Thesis_Joris_Van_Bogaert.

Thesis_Joris_Van_Bogaert.
Assessment of Potential Fuel
Saving Benefits of HybridElectric Regional Aircraft
Technische Universiteit Delft
Joris Van Bogaert
A SSESSMENT OF P OTENTIAL F UEL S AVING
B ENEFITS OF H YBRID -E LECTRIC R EGIONAL
A IRCRAFT
by
Joris Van Bogaert
in partial fulfillment of the requirements for the degree of
Master of Science
in Aerospace Engineering
at the Delft University of Technology,
to be defended publicly on Thursday December 17, 2015.
Supervisor:
Thesis committee:
Dr.ir. Mark Voskuijl
Dr. Arvind G. Rao
Dr. Hans Mulder
Simon Tayler
TU Delft
Fokker Elmo
This thesis is confidential and cannot be made public until December 31, 2015.
An electronic version of this thesis is available at http://repository.tudelft.nl/.
Thesis registration number: 068#15#MT#FPP
P REFACE
This thesis presents the research done in investigating the potential reduction in fuel consumption
that can be achieved by utilizing a hybrid-electric power plant in aircraft. It has been written to
fulfill the requirements for the degree of Master of Science in Aerospace Engineering at the Delft
University of Technology. The research described herein was conducted under the supervision of
Dr.ir. Mark Voskuijl and Dr. Arvind G. Rao.
First and foremost, I would like to thank my supervisors for their excellent guidance, support
and feedback during this process. Thanks also to my friends and colleagues at the TU Delft, it was
always helpful to discuss ideas about my research with you. Finally, I take this opportunity to express
my gratitude to my family and girlfriend for their love, unfailing encouragement and support.
Joris Van Bogaert
Delft, December 2015
iii
S UMMARY
Both NASA and the EU have set ambitious goals in terms of aircraft emission reduction. Previous
studies have indicated that these goals can not be met with evolutionary improvements of conventional technologies. For this reason there is a need for revolutionary aircraft concept and/or radical
innovative systems. One such concept is the use of a hybrid-electric propulsion system.
The aim of this project is to investigate the potential improvements in fuel consumption of a
hybrid-electric regional aircraft which uses both batteries and conventional fuel as power source.
Since no comprehensive design studies of such a concept have been performed so far, the design
space is explored as well.
All designs considered in this project are constructed for the year 2035, because the current
level of technological progress is not adequate for a hybrid-electric aircraft to be feasible. By the
year 2035 it is expected that lithium-air battery technology will mature and a battery specific energy
of 750 Wh/kg to 1500 Wh/kg can be expected. Also, high-temperature superconducting technology
in wiring, electric motors and other electronics are predicated to be viable. The study is limited to
regional aircraft because the required range of larger aircraft can not be met, even with the expected
technological improvements.
Many different power train architectures are possible using both batteries and conventional fuel,
most notably the series-hybrid architecture and the parallel-hybrid architectures. It is chosen to use
the parallel-hybrid architecture in all designs due to its potential for a lower weight and versatility
in operating modes. Using this architecture, two operating modes are considered: the power split
operating mode and the constant gas turbine power operating mode. The power split operating
mode requires a certain power split as input for each flight phase which determines how the gas
turbine and electric motor are used during that flight phase. The constant gas turbine operating
mode requires a maximum continuous gas turbine power as input. This gas turbine is then used
as efficiently as possible during the mission and the electric motor is used when more power is
required.
Since several designs have to be generated in order to explore the design space, a program is
needed which can generate a preliminary aircraft design based on a set of input parameters in a
relatively short time span. For this purpose a (mostly) physics-based preliminary design program
called "Initiator" is used. This program is heavily adapted in order to be able to generate regional
hybrid-electric aircraft designs. Especially the mission analysis is heavily modified. First of all, this
adapted program is used to generate a reference aircraft,based upon the ATR 72-600. The reference aircraft is subsequently compared to its real-life counterpart in order to validate some of the
changes made to the "Initiator" program. It is found that the reference aircraft is a very close match
to the ATR 72-600 in terms of mass breakdown, geometry and performance. The changes pertaining to the hybrid-electric aircraft can not be validated since no comparable design studies have been
performed so far.
Subsequently, the effect of making a design more hybrid (increasing the degree of hybridization
or the supplied power ratio) is investigated for multiple battery specific energies. It is found that
for a range of 1528 km, the fuel weight decreases with an increasing supplied power ratio, for any
battery specific energy between 750 Wh/kg and 1500 Wh/kg. At the same time, the MTOM increases.
This holds true for a range up to around 5000 km (depending on the chosen battery specific energy).
After which either no benefit can be achieved from using a hybrid-electric aircraft or there exists an
optimum in the supplied power ratio. This is because, after a certain point, more energy is required
v
vi
P REFACE
to transport the batteries than the energy stored in the batteries itself. There is also a limit to the
maximum achievable supplied power ratio for most battery specific energy/range combinations.
After a certain point the MTOM (and thus also the energy requirement) increases to such a level
that no more feasible design is possible.
Comparing both operating modes shows that the constant gas turbine operating mode gives
more optimal results compared to using a constant power split over the entire mission. There is a
slight decrease in fuel weight for the same MTOM and battery weight due to the lower average SFC.
Using a constant power split over the entire mission might not be optimal, however, no optimal
power split has been found so far. This might be a topic for further study.
Lastly, one final regional hybrid-electric aircraft is selected from the design space using a battery
specific energy of 1000 Wh/kg and a supplied power ratio of 0.34. This was chosen as being a feasible, realistic design point which does not require too large technological improvements in order
to be feasible. This design point results in fuel weight reduction of 28 % compared to the reference
aircraft, while having an increase in MTOM of 14 %. From this it can be concluded that significant
fuel weight reduction can be achieved by using the hybrid-electric aircraft concept. However, the
exact figure of how much benefit can be achieved is highly dependent on the level of technological
progress between now and 2035. In particular the battery specific energy has a large influence.
C ONTENTS
List of Figures
ix
List of Tables
xiii
1 Introduction
2 Project Description
2.1 Configuration and Requirements .
2.2 Technology Overview . . . . . . .
2.2.1 Battery Technology . . . . .
2.2.2 Electric Motor Technology .
2.3 Power plant Architecture. . . . . .
2.3.1 Architecture Possibilities . .
2.3.2 Selected Architecture . . . .
2.4 Control Strategies . . . . . . . . .
2.5 Important Parameters . . . . . . .
1
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
3 Methodology
3.1 Initiator . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2 Reference Aircraft Design . . . . . . . . . . . . . . . . . .
3.2.1 Engine and Propeller Sizing . . . . . . . . . . . . .
3.2.2 Gas turbine power and fuel consumption variation
3.2.3 Other Modifications . . . . . . . . . . . . . . . . .
3.3 Class 2 Battery and Fuel Sizing . . . . . . . . . . . . . . .
3.3.1 Battery Sizing . . . . . . . . . . . . . . . . . . . . .
3.3.2 Fuel . . . . . . . . . . . . . . . . . . . . . . . . . .
3.4 Class 2.5 Battery and Fuel Sizing . . . . . . . . . . . . . .
3.4.1 Take-off . . . . . . . . . . . . . . . . . . . . . . . .
3.4.2 Climb . . . . . . . . . . . . . . . . . . . . . . . . .
3.4.3 Cruise . . . . . . . . . . . . . . . . . . . . . . . . .
3.4.4 Descent . . . . . . . . . . . . . . . . . . . . . . . .
3.4.5 Landing . . . . . . . . . . . . . . . . . . . . . . . .
3.4.6 Hold/Loiter . . . . . . . . . . . . . . . . . . . . . .
3.5 Comparison between Class 2 and Class 2.5 sizing . . . . .
3.5.1 Mission analysis results . . . . . . . . . . . . . . .
3.5.2 Comparison . . . . . . . . . . . . . . . . . . . . . .
3.6 Electric Motor Sizing . . . . . . . . . . . . . . . . . . . . .
3.7 Wiring . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.8 Other Components. . . . . . . . . . . . . . . . . . . . . .
3.9 Component Placement . . . . . . . . . . . . . . . . . . .
3.10 Implementation . . . . . . . . . . . . . . . . . . . . . . .
3.11 Limitations . . . . . . . . . . . . . . . . . . . . . . . . . .
vii
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
3
3
5
5
9
10
10
11
13
14
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
15
15
17
17
19
23
23
23
25
28
32
36
39
42
44
46
48
48
51
52
53
54
55
56
56
viii
4 Results
4.1 Reference Aircraft . . . . . . .
4.2 Hybrid Aircraft . . . . . . . . .
4.2.1 Inputs . . . . . . . . . .
4.2.2 Supplied Power Ratio. .
4.2.3 Operating Modes . . . .
4.2.4 Optimal Power Split . .
4.3 Sensitivity Analysis . . . . . . .
4.3.1 Range . . . . . . . . . .
4.3.2 Battery specific energy .
4.4 Final Design . . . . . . . . . .
C ONTENTS
.
.
.
.
.
.
.
.
.
.
59
59
62
62
63
68
74
77
77
79
79
5 Conclusion & Recommendations
5.1 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.2 Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
83
83
84
A Derivation of hybrid-electric range equation
85
Bibliography
87
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
L IST OF F IGURES
2.1
2.2
2.3
2.4
2.5
Impression of the EuroFlyer aircraft concept [1] . . . .
Critical temperature of superconducting materials [2]
Series hybrid architecture . . . . . . . . . . . . . . . . .
Parallel hybrid architecture . . . . . . . . . . . . . . . .
Architecture of the power plant . . . . . . . . . . . . . .
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
3.1 Simplified flow chart showing the basic workings of the initiator program . . . .
3.2 Example of a power loading diagram of an aircraft comparable to the ATR72-600
3.3 Power variation as a function of velocity and altitude [3] . . . . . . . . . . . . . . .
³ ´0.75
ρ
3.4 Slope of PP0 compared to the slope of ρ 0
for a velocity of 250 knots . . . . . .
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
4
9
10
11
12
. . .
. . .
. . .
16
18
20
. . .
20
3.5 Fuel flow as a function of velocity and altitude [3] . . . . . . . . . . . . . . . . . . . . . .
3.6 SFC as a function of velocity and altitude [3] . . . . . . . . . . . . . . . . . . . . . . . . .
3.7 SFC variation with power setting for a typical cruise condition with V = 200 knots and
h = 20000 ft (= 6096 m) [3] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.8 Results of the adapted Brequet range equation for a variable fuel weight and power split
3.9 Example of a typical mission profile that can be used to determine the battery and fuel
weight . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.10 Activity diagram of the flight phases of the Mission Analysis module . . . . . . . . . . .
3.11 Altitude, speed and flight path angle of an arbitrary hybrid-electric aircraft during
take-off . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.12 Flow chart of the take-off phase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.13 Graph of the shaft power, gas turbine power and electric motor power during the climb
phase with a power split of 0.5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.14 Altitude, speed and flight path angle of an arbitrary hybrid-electric aircraft during the
climb phase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.15 Flow chart of the climb phase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.16 Altitude, speed and flight path angle of an arbitrary hybrid-electric aircraft during the
cruise phase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.17 Flow chart of the cruise phase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.18 Altitude, speed and flight path angle of an arbitrary hybrid-electric aircraft during the
descent phase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.19 Flow chart of the descent phase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.20 Altitude, speed and flight path angle of an arbitrary hybrid-electric aircraft during
landing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.21 Flow chart of the landing phase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.22 Flow chart of the loiter phase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.23 State of an arbitrary hybrid-electric aircraft during the entire mission, including deviation and loiter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.24 Shaft -, gas turbine - and electric motor power during the entire mission for a constant
power split of 0.5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.25 Battery- and fuel weight used during the entire mission, for a constant power split of 0.5
ix
21
21
22
27
28
31
34
35
37
37
38
40
41
43
43
44
45
47
49
50
50
x
L IST OF F IGURES
3.26 Variation of the electric motor and cryocooler weight with respect to the maximum
electric motor power . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.27 Cable weight as a function of current for a cable rated at 6 kV . . . . . . . . . . . . . . .
4.1
4.2
4.3
4.4
4.5
4.6
4.7
4.8
4.9
4.10
4.11
4.12
4.13
4.14
4.15
4.16
4.17
4.18
4.19
4.20
4.21
4.22
4.23
4.24
4.25
4.26
Front view of the ATR72-600 compared to the reference aircraft . . . . . . . . . . . . . .
Side view of the ATR72-600 compared to the reference aircraft . . . . . . . . . . . . . .
Top view of the ATR72-600 compared to the reference aircraft . . . . . . . . . . . . . . .
Battery mass vs supplied power ratio for multiple battery energy densities . . . . . . .
Fuel mass vs supplied power ratio for multiple battery energy densities . . . . . . . . .
Maximum take-off mass vs supplied power ratio for multiple battery energy densities
Maximum electric motor power vs supplied power ratio for multiple battery energy
densities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
The mass of the components making up the electrical part of the powertrain (minus
the batteries) vs supplied power ratio for a battery energy density of 1500 Wh/kg . . .
mass of the gas turbine vs supplied power ratio for multiple battery energy densities .
The maximum continuous gas turbine power vs the supplied power ratio for battery
energy densities of 750, 1000 and 1500 Wh/kg . . . . . . . . . . . . . . . . . . . . . . . .
Shaft -, electric motor - and gas turbine power during the entire mission for a constant
power split, resulting in a supplied power ratio of 0.25 using a battery specific energy
of 1000 Wh/kg. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Shaft -, electric motor - and gas turbine power during the entire mission for a certain
input gas turbine power, resulting in a supplied power ratio of 0.25 using a battery
specific energy of 1000 Wh/kg. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Difference in fuel mass for the constant gas turbine power operating mode compared
to the power split operating mode using a battery specific energy of 750, 1000 and 1500
Wh/kg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Difference in battery mass for the constant gas turbine power operating mode compared to the power split operating mode using a battery specific energy of 1000 and
1500 Wh/kg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Difference in maximum electric motor power for the constant gas turbine power operating mode compared to the power split operating mode using a battery specific
energy of 750, 1000 and 1500 Wh/kg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Difference in gas turbine mass for the constant gas turbine power operating mode
compared to the power split operating mode using a battery specific energy of 750,
1000 and 1500 Wh/kg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Difference in MTOW for the constant gas turbine power operating mode compared to
the power split operating mode using a battery specific energy of 750, 1000 and 1500
Wh/kg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Optimum power split using model predictive control [4] . . . . . . . . . . . . . . . . . .
Optimum power split input variation 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Optimum power split input variation 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Fuel and battery mass vs supplied power ratio for designs with constant power split
and the optimum power split according the Perullo et al. . . . . . . . . . . . . . . . . .
Fuel and battery mass vs supplied power ratio for designs with constant power split
and the optimum power split according the Perullo et al. . . . . . . . . . . . . . . . . .
MTOW vs supplied power ratio for designs with constant power split and the optimum
power split according the Perullo et al. . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Variation of fuel mass with supplied power ratio for multiple ranges . . . . . . . . . . .
Variation of maximum take-off mass with supplied power ratio for multiple ranges . .
Fuel mass vs battery specific energy for multiple supplied power ratios . . . . . . . . .
53
54
60
60
61
64
65
65
66
66
67
68
69
69
71
71
72
72
73
74
75
75
76
76
77
78
78
79
L IST OF F IGURES
4.27
4.28
4.29
4.30
Isometric view of the hybrid-electric aircraft
Front view of the hybrid-electric aircraft . .
Side view of the hybrid-electric aircraft . . .
Top view of the hybrid-electric aircraft . . .
xi
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
81
81
81
82
L IST OF TABLES
2.1 Estimation of battery parameters by the year 2035 . . . . . . . . . . . . . . . . . . . . .
3.1 Parameters the state matrix ’S’ keeps track of . . . . . . . . . . . . . . . . . . . . . . . . .
3.2 Comparison between the class 2 and class 2.5 sizing methods for constant power splits
ranging from 0.00 to 1.00 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.3 Comparison between the class 2 and class 2.5 sizing methods for input gas turbine
powers ranging from 0.1 MW to 3 MW . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.4 New input parameters that are needed in the Initiator program when designing a hybridelectric aircraft . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.1 Requirements of the ATR 72-600 which are also used as input for the reference aircraft
design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.2 Parameters comparing the ATR 72-600 to the reference aircraft . . . . . . . . . . . . . .
4.3 Input values that are used for each design considered in this chapter . . . . . . . . . .
4.4 Parameters comparing the hybrid-electric aircraft to the reference aircraft . . . . . . .
4.5 Parameters comparing the geometry of the hybrid-electric aircraft to the reference aircraft . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
xiii
8
29
51
52
58
59
62
62
80
80
N OMENCLATURE
Acronyms
ACARE Advisory Council for Aviation Research and Innovation in Europe
AVL
Athena Vortex Lattice
FF
Fuel fraction
HTS
high-temperature super-conducting
IEEE
Institute of Electrical and Electronics Engineers
KEAS Knots equivalent airspeed
LTS
Low-temperature super-conducting
MEA
More-Electric-Aircraft
[kts]
MTOM Maximum take-off mass
[kg]
SFC
Brake specific fuel consumption
[g/KWh]
SOC
State of charge
SRIA
Strategic Research and Innovation Agenda
UAV
Unmanned Aerial Vehicle
Subscripts
bat
Battery
el ec
Electrical wiring and inverter
em
Electric motor
0
Sea-level condition
avg
Average
cable Cable
climb State during the climb phase
cryo
Cryocooler
disk
Propeller disk
endcruise State at the end of the cruise phase
gasturb Gas turbine
precruise State at the beginning of the cruise phase
xv
xvi
prop
L IST OF TABLES
Propeller
take-off State during the take-off phase
tot
total
Symbols
∆
Change in ...
Q̇
Heat transfer rate
η
Efficiency
γ
Flight path angle
Φ
Supplied power ratio
ρ
Density
[ m3 ]
A
Area
[m 2 ]
e
Specific energy
[Wh/kg]
p
power density
[kW/kg]
v
Power to volume ratio
[kW/l]
vol
Volumetric energy density
[Wh/l]
a
Speed of sound
b
Wing span
[m]
D
Drag
[N]
d
Diameter
[m]
E
Energy
f
Frequency
g
Gravitational acceleration
H
Degree of hybridization
h
Altitude
[m]
L
Lift
[N]
l
Length
[m]
m
Mass
[kg]
N
number
P
Power
Q
Heat energy
[-]
[W]
[-]
[deg]
[-]
kg
[m/s]
[Wh]
[Hz]
[m
]
s2
[-]
[W]
[J]
L IST OF TABLES
R
Range
S
Power split
T
Thrust
t
time
U
Voltage
V
Speed
xvii
[km]
[-]
[N]
[sec]
[V]
[m/s]
1
I NTRODUCTION
The Strategic Research and Innovation Agenda (SRIA) of ACARE [5] as well as the NASA N+3 [6]
goals have set ambitious targets in terms of emission reduction for the aviation industry. Within
SRIA 2035 it is recommended that 51% CO2 emission reduction should result from improvements
of propulsion systems and airframes, while NASA N+3 sets a goal of a 60% fuel burn reduction by
2025 [7].
Continuous improvements of conventional technologies will not be enough to fulfil these ambitious requirements. The project SELECT [8] (contracted by Northrop Grumman for NASA) demonstrated that the NASA N+3 goals could not be met with evolutionary improvements of conventional
technologies. For this reason there is a need for revolutionary aircraft concepts and/or radical innovative systems.
One such concept is to use a hybrid-electric propulsion system. This propulsion system uses
both batteries (or some other source of electric energy such as fuel cells) and conventional fuel to
power the aircraft. This has the possibility of significantly reducing emissions and fuel burn.
The aim of this project is to investigate the potential fuel saving (and thus also emission reduction) hybrid-electric regional aircraft can achieve by the year 2035. No comprehensive design study
of hybrid-electric aircraft have been performed so far, all previous design studies were either very
limited in scope or performed for small UAV’s. As such, in order to find out what the potential fuel
saving is, the design space is explored as well. This is done by adapting an existing physics-based
conceptual design program in order for it be able to design hybrid-electric aircraft. The scope of
this project is limited to regional aircraft since the technology in the year 2035 is not expected to be
sufficient for larger aircraft with a longer range to be achievable.
First of all, in Chapter 2, the project is further explained, in particular what kind of configuration
and technologies will be used in the hybrid-electric aircraft designs as well as what control strategies
can be employed. The methodology of how a design is generated is explained in Chapter 3 and in
Chapter 4 the results of the design study are expanded upon. Finally, in Chapter 5, the conclusion
and recommendations for future work are presented.
1
2
P ROJECT D ESCRIPTION
In this chapter the aim of the project is further explained, as well as an investigation into what technological advancement can be expected by the year 2035. Some different power plant architectures
are discussed and one of the architectures is selected as a baseline. Subsequently the used operating modes are briefly explained (i.e. how it is determined when how much of what power source is
used) and the most important parameters are presented.
2.1. C ONFIGURATION AND R EQUIREMENTS
The aim of this project is to investigate the decrease in fuel consumption a hybrid-electric aircraft
concept could have as compared to a conventional aircraft by the year 2035. Since almost no comprehensive design studies pertaining to hybrid-electric aircraft have been performed so far, the design space is explored as well. The design studies that were performed are limited in scope or only
applicable for small UAVs [9] [10] [11] [12].
A hybrid-electric propulsion system is defined as a propulsion system in which the energy for
propulsion is carried in two or more kinds or types of energy sources, or converters, and at least
one of them can deliver electrical energy [13]. In this project we only consider two power sources:
one conventional gas turbine and one electric motor powered by batteries. Using these two power
sources many different power plant architectures are possible, which are discussed in Section 2.3.
The configuration of the hybrid-electric concept under investigation is based upon the Euroflyer
[1]: a novel aircraft configuration developed during the 2013 Design Synthesis Exercise at the Delft
University of Technology. Figure 2.1 shows an artist’s impression of the final Euroflyer design. The
hybrid-electric aircraft configuration is meant to incorporate the same basic elements:
• Boundary layer ingestion due to push-prop located at the rear of the fuselage which ingests
part of the boundary layer around the fuselage in order to reduce drag.
• Contra-rotating propellers which not only offset the torque created by the propeller but also
have the possibility of increasing the efficiency of the propeller at the cost of extra noise generation 1 and added mechanical complexity.
In this project however only the impact of the hybrid-electric propulsion system is examined. The
impact of the contra-rotating propeller and boundary layer ingestion will not be taken into account
since this is outside the scope of the project and would need to be investigated in further studies.
1 The extra noise generation can be cancelled out by adding a shroud around the propellers as is done in the Euroflyer
concept
3
4
2. P ROJECT D ESCRIPTION
Figure 2.1: Impression of the EuroFlyer aircraft concept [1]
In order to compare the performance of a hybrid-electric aircraft to a conventional aircraft a
baseline aircraft is developed as well. This reference aircraft will be based upon the ATR-72-600.
To be able to make a good comparison, the requirements for the hybrid-electric design will be the
same as those for the ATR-72-600. These requirements are also similar to those for the Euroflyer [1].
These requirements are as follows:
• Range:
1528 km
• Number of passengers:
68
• Payload weight:
7500 kg
• Cruise Mach:
0.45
• Cruise altitude:
7500 m
The reason for designing a regional aircraft and not a larger aircraft with longer range is because the
technology in 2035 is not expected to be adequate for a larger aircraft with such a propulsion system
to be feasible. However, the influence on range will also be examined to determine what the range
limit of a hybrid-electric regional aircraft is as well as what factors influence it.
2.2. T ECHNOLOGY O VERVIEW
5
2.2. T ECHNOLOGY O VERVIEW
In this section a brief overview is given of the technologies that are required in order for a hybridelectric aircraft to be feasible, as well as the expected technological progress between now and 2035.
This mainly pertains to the battery technology and the electric motor technology. While it is expected that other technology such as the gas turbine technology will also improve between now
and 2035, this is not taken into account during the course of this project.
2.2.1. B ATTERY T ECHNOLOGY
One of the main hurdles to overcome before hybrid regional aircraft become feasible is the battery
technology. The energy density of today’s batteries is simply not high enough to make hybrid electric propulsion viable for anything larger than ultra-light aircraft or UAV’s. Luckily there is a lot of
research being done in this field (which will be discussed later), especially with the growth in the
electric car market.
Although specific energy is probably the most important criteria for evaluating battery performance in aircraft it is certainly not the only criterion. Below is a list of the main performance metrics
necessary for a good evaluation and comparison:
• Specific energy (e bat )
[Wh/kg]
• Volumetric energy density (vol bat )
[Wh/l]
• Power density (p bat )
[W/kg]
There are also other metrics that have to be considered such as safety and charging performance, as well as any other possible systems that have to be implemented, such as battery cooling.
Safety entails everything from explosion hazard to overheating hazard. It is very hard to make an
estimation of the magnitude of such hazards for technology that is still in its infancy. For this reason
this performance metric has not been investigated any further. Charging performance is also an
important metric for which no accurate prediction can be done at this time.
In this section an overview of the most important battery technologies currently under development is given. Their respective advantages and disadvantages are also listed as well as the future
prospects of the battery technologies. Since the aircraft under consideration is being developed
for a 2035 timeframe, it is necessary to make an estimation of how battery technology will evolve
and mature. To make a hybrid-electric aircraft viable a certain battery specific energy density will
be needed which is much higher than today’s. Boeing determined the specific energy density of
battery systems would need to be 750 Wh/kg or greater in order for a hybrid aircraft to be a realistic option [7]. Battery energy density increases every year with about 6% [14], however, sometimes
there are big jumps when new technology becomes available. This means that it is very hard or even
impossible to make accurate predictions for where battery technology will be by 2035. As such, in
this project a wide range of battery specific energies is examined.
L ITHIUM ION
Lithium ion is the main battery technology, used for high performance applications such as vehicles
or portable electronic devices. Although this technology is already mature, every year there is still
an increase in energy density of about 6% [14]. This increase is mainly due to improvements in
fabrication, using lighter cases (such as aluminium instead of stainless steel) or by optimization of
the cell design [15]. This trend is expected to continue for the foreseeable future until an energy
density of around 250 Wh/kg is reached [14].
Some companies such as Envia Systems state that they have achieved lithium-ion batteries with
a specific energy of 400 Wh/kg [16]. However the author could not find reliable sources for these
claims and no additional information is available.
6
2. P ROJECT D ESCRIPTION
Since lithium-ion technology is already very mature compared to the other technologies, not
much improvement in energy density is possible for this technology. In the not so distant future a
specific energy 250 Wh/kg can be achieved [15]. How it will evolve further is not known. Most authors expects this technology to not be capable of higher energy densities than around 350 Wh/kg,
most likely not enough to make a hybrid regional aircraft viable. Based on trends of existing lithiumion batteries, the volumetric energy density is about 1.7 times higher than the specific energy for
lithium-ion batteries. This technology, while cutting edge at the moment, will probably be obsolete
by 2035 for high performance applications.
L ITHIUM SULPHUR
An emerging battery technology is Lithium-sulphur batteries. This is at the time of writing the most
researched emerging battery technology with more than 450 papers published on this topic in less
than 2 years [17]. In lithium-sulphur cells the following reaction takes place:
2Li + S —> Li 2 S
This reaction results in a theoretical specific energy of 3730 Wh/kg. Almost an order of magnitude
higher than that of common lithium-ion battery cells [18]. Of course the practical specific energy
will be far less because of the added mass of the housing and other components. Sulphur also has
the added benefit of being cheap and abundant, thus also promising a major improvement in not
only specific energy but also cost [17]. Nevertheless there are still some major issues to be overcome
before this battery technology can become mainstream [18]:
• The discharge process of Lithium-sulphur cells proceeds through the sequential formation of
polysulphides (Li x S y ) which easily dissolve in the liquid carbonate electrolyte solutions and
eventually diffuse to the lithium anode resulting in severe corrosion effects. This results in
the loss of active materials, low overall efficiency and large capacity decay after a number of
cycles.
• The low electronic conductivity of S, Li 2 S and the intermediate Li-S products, severely affecting the charge rate capability of the battery.
• The use of lithium metal as the anode, which can cause serious safety risks due to uneven
deposition upon charge, and can result in a short circuit in the cell, which in turn can result
in thermal runaway and, eventually, fires or explosions.
However, many breakthroughs have happened in a very short timespan. These developments resulted in Lithium-sulphur batteries being used in practical applications, not only laboratory experiments. One such example is the long endurance UAV "Zephyr" which set the record for longest
unmanned flight by staying aloft for 54 hours. This was partially possible due to the lithium-sulphur
batteries it carries. These batteries have a specific energy of 350-380 Wh/kg, much higher than any
lithium-ion battery available today. Although these batteries are extremely high performance, the
number of recharge cycles is still limited (exact figures are not available) [19]. In a lab environment
lithium-sulphur batteries with a specific energy of 500 Wh/kg have been demonstrated. On top of
that they had a cycle performance of up to 1500 cycles [20].
The main R&D focus for lithium-sulphur batteries lies on improving the cycle life performance.
Based on development goals of Sion Power it is expected that batteries with an acceptable cycle life
(>1000 cycles) will be commercially available by 2020 [21] [14]. Sion power also states that specific
energies of around 550-650 Wh/kg at cell level would be available by then [21]. This is considerably
higher compared to for lithium-ion batteries. Specific power is expected to be at least 400 W/kg.
[14].
2.2. T ECHNOLOGY O VERVIEW
7
L ITHIUM A IR
Another novel battery technology is lithium-air batteries. This technology is still in its infancy, yet
lab prototypes show promising results. Lithium-air uses oxygen as oxidizer so it does not have to
take the oxidizer with it. This results in much higher theoretical energy densities up to 11680 Wh/kg
[22]. However, practical energy densities for Li-air batteries will be far less. Existing metal-air batteries, such as Zn/air, typically have a practical energy density of about 40-50% of their theoretical
density. However, one can safely assume that even fully developed Li-air cells will never achieve
such an excellent ratio, because lithium is very light, and therefore the overhead of the battery structure, electrolytes, and so forth will have a much larger impact [22]. But, using air as the oxidizer also
means that during discharge the batteries actually increase in weight. The reaction for non-aqueous
lithium-air batteries is as follows:
2Li + O 2 —> Li 2O 2
Considering the chemistry of this reaction, the increase in weight can be estimated as follows [19]
[22]:
• Reaction Potential Li 2O 2 :
3.1 V
• Faraday constant:
96485 C/mol
• Specific mass O 2 :
0.016 kg/mol
kg
∆m =
C
0.016 mol · 3600 Ah
3.1V
C
· 96485 mol
= 1.92 · 10−4
kg
Wh
(2.1)
Lithium-air technology is still in the early developmental stages, with practical results falling far
short of theoretical calculations. The best reported lab cell has achieved a specific energy of only
363 Wh/kg [23].
As mentioned before, quite a few challenges remain before lithium-air batteries can be a viable
power source. The most important research topics that still remain are [23] [22]
• Better understanding of the electrochemical reactions and their relationship to the discharge/charge
currents. This is vital for demonstrating chemical reversibility and understanding the efficiency of the battery.
• Development of oxidation-resistant electrolytes and cathodes. This is also very important for
chemical reversibility and efficiency in the battery cycling.
• Understanding the nature of electrocatalysis for Li-air batteries and the development of costeffective catalysts. This is key to enhancing power density in discharge and electrical efficiency in a discharge-charge cycle.
• Development of new air cathodes that optimize transport of all reactants to the active catalyst
surfaces and provide appropriate space for solid lithium oxide products. This is required to
maintain capacity at higher power densities.
• Development of a lithium metal or lithium composite electrode capable of repeated charging
and discharging at higher current densities.
• Development of high throughput air-breathing system that separates O 2 from ambient air in
order to avoid H2 O, CO 2 , and other environmental contaminants from limiting the lifetime of
Li-air batteries.
8
2. P ROJECT D ESCRIPTION
• Understanding the origin of the temperature dependencies in Li-air batteries and minimizing
their adverse effects.
There is no scientific consensus on if or when the above mentioned problems might be resolved
and what the expected gravimetric energy density might be in a 2035 timeframe. Below is a list of
some of the most important authors and what their predictions are in terms of energy density by
2035.
• Kuhn et al.
1000-1500 Wh/kg [24] [25]
• S. Stückl et al.
750–2000 Wh/kg [19]
• L. Johnson
2000 Wh/kg [26]
• K. Rajashekara
2000 to 3500 Wh/kg [27]
The wide discrepancy between the figures demonstrates that the uncertainty is very large and there
are still many unknowns. However, figures given by K. Rajashekara seem too optimistic. The volumetric energy density can also be expected to lie within approximately the same range. Johnson
also predicts the power density to be in the range of 400 to 640 W/kg [26]. There is also no scientific
consensus whether this technology will achieve market readiness by 2035. While NASA states that,
based on past development cycles, it is unlikely that the technology will be mature by the N+3 time
frame [28], IBM states that the technology is expected to be consumer ready by 2030 [22].
O VERVIEW AND CONCLUSION
Table 2.1 gives an overview of the parameters for each of the technology options discussed in this
section. All of the values are rough estimations for the year 2035 and will most likely not be very
accurate. However, they can provide a good basis for comparison of the various technologies.
The last column represents the technology readiness level (TRL). This is a metric for how mature
the technology is at this time. It is represented in a scale from 1 to 9 with 1 being where just the
theoretical principles are observed and 9 being a system that is proven in extensive operation. In
this case the definition by NASA is used [29].
Table 2.1: Estimation of battery parameters by the year 2035
Type
Lithium-Ion
Specific
[Wh/kg]
350
Lithium-Sulfur
Lithium-Air
> 650
750-2000
energy
Volumetric energy
density [Wh/l]
590
> 460
750-2000
Power density [W/kg]
TRL
400-450 (rough estimation)
> 400
400-640
9
5
3
If the conclusion by Boeing that an energy density of at least 750 Wh/kg is needed is correct than
it would appear that lithium-air batteries are the only option, except if lithium-sulphur batteries
achieve a greater energy density than is currently expected. The main problem with lithium-air
batteries is whether the technology will be ready by 2035. Since lithium-ion batteries took at least
20 years to achieve TRL 9 it is likely that lithium-air will need approximately the same amount of
time to achieve maturity [28].
For the designs considered in this study a wide range of battery specific energies is used: between 750 Wh/kg and 1500 Wh/kg. Since most sources agree that this is a realistic range for lithiumair batteries. A sensitivity study is also performed to figure out the behaviour of the design with
changing energy density (Section 4.3.2).
2.2. T ECHNOLOGY O VERVIEW
9
2.2.2. E LECTRIC M OTOR T ECHNOLOGY
Current electric motors are mainly used in vehicles such as cars, not in aircraft. For aircraft propulsion the required shaft power is an order of magnitude higher than the high power density motors in
use today. Scaling up these motors leads to unfavourable trends related to physical sizing laws. With
growing motor size the ratio of outer (cooling-) surface to internal motor volume gets worse, this is
detrimental for efficient heat dissipation. In ground based applications such as power plant generators this problem is addressed by using oversized conductor cross sections to minimize heat loss.
Because this requires very heavy and bulky motor layouts, this design is not practical for aerospace
applications [19].
This problem can be solved by using high-temperature super-conducting (HTS) motors [30].
Superconducting materials have the unique property of being able to carry current with almost no
resistive losses. This property only occurs when the superconducting material is below a certain
critical temperature, magnetic field and current density level [2].
In the past, reaching these critical temperatures was extremely expensive and thus not practical.
However, more recently high-temperature superconducting materials have been discovered which
have a much higher critical temperature, above the boiling point of liquid nitrogen (77 K). Figure 2.2
shows the critical temperature of superconducting materials and their respective date of discovery.
Figure 2.2: Critical temperature of superconducting materials [2]
These superconducting motors can eliminate many of the problems related to upscaling conventional motors. A study was carried out comparing a 4480 KW HTS motor to a conventional induction motor. It was found that the load loss (heat produced) at full power amounted to 40 % that
of the conventional motor which leads to much higher efficiency. On top of that the HTS motor had
a 50 % volume reduction and it was found that the HTS motor would weigh around 70 % that of
the conventional motor resulting in a much higher power density [2] [28]. Current superconducting
motors have a power density comparable to turbine engines while fully developed superconducting
engines have the potential of being 3 times lighter [31].
Supercooling a motor takes power. For a low temperature superconducting motor it takes about
1.2 % of the rated power to run the cryocooler, while for a HTS motor this cryocooler only uses 0.16
% of the rated power. This is due to the much lower temperatures that must be sustained to reach
the LTS critical temperature [2] [28]. Another disadvantage of HTS motors is the added complexity
of the system. Other systems have to be added such as a cryocooling system and an inverter [28].
There are still challenges that remain before this technology is ready for use in commercial aircraft. The main hurdle that needs to be overcome is the insufficient power to weight ratio for the
technology to be practical. The cold heads for the cryocooling system currently have an energy density of around 3 kg/kW-input and the compressor has an energy density of about 15 kg/kW-input
10
2. P ROJECT D ESCRIPTION
[28]. It would be desirable to reduce the combined cold head and compressor weight to around 3
kg/kW-input [28] [31]. This may be possible for aircraft entering into service around 2035 [31]. It has
also been estimated that the needed power to weight ratio for the electric motor would be around
25 kW/kg and around 50 kW/kg for the generators [31].
Another issue is that the latest generation of HTS wiring is not yet available in long lengths and
the first generation wiring is extremely expensive (around 40 % of the total motor cost) [2]. Another
problem that has to be overcome is that DC HTS motors meet the low loss requirement, however it
hasn’t been demonstrated yet that low loss AC conductors can be developed in the future. Experts
predict that a loss of less than 10 W/A-m is needed [28].
The cryogenic cooling system also provides some challenges, namely cryogenic pipe leakage,
the Carnot efficiency and a higher reliability of the system. A reliability of 99.8 % needs to be
achieved [32].
When these challenges are solved HTS engines can be used in aerospace applications. Although
these challenges are substantial (especially the large jump in power to weight ratio required) NASA
is confident that we will see this technology in commercial aircraft by 2035 [28].
2.3. P OWER PLANT A RCHITECTURE
2.3.1. A RCHITECTURE P OSSIBILITIES
Many distinct power plant architectures are possible for a hybrid electric propulsion system. The
most commonly used are the series-hybrid architecture and the parallel-hybrid architecture.
The series powertrain configuration, shown in Figure 2.3 is the simplest of all the possible configurations. The propeller shaft is only driven by the electric motor. The gas turbine is used to either
charge the batteries or provide auxiliary power to drive the electric motor [33]. This means the gas
turbine can continuously operate at its most efficient point, thereby reducing fuel consumption and
emissions. For commercial ground vehicles this configuration even has the lowest fuel consumption of all the configurations mentioned in this section [34].
Gas turbine
Generator
Electric
motor
Power
converter
Figure 2.3: Series hybrid architecture
Another advantage is that the gas turbine can generally be sized smaller because it only needs to
meet average power demands. However, in order to meet peak power demands, the electric motor
and battery need to be sized larger than in other configurations. This, combined with the need
for a generator, results in a significant weight penalty compared to the parallel configuration [12]
[35]. This is not such a big problem for ground vehicles, but for aircraft this can be a major issue.
Additionally, because the mechanical energy from the gas turbine is first converted to electrical
energy then passed to the electric motor and converted once again to mechanical energy to drive
2.3. P OWER PLANT A RCHITECTURE
11
the propeller, there exist large conversion losses between the mechanical and electrical systems [35].
In the parallel-hybrid configuration both the mechanical power output and the electrical power
output are connected in parallel to drive the transmission as shown in Figure 2.4. An advantage of
this configuration is that it requires only two propulsion devices, where either the electric motor
and/or the gas turbine can be downscaled without a loss in maximum power [12]. This result in the
smallest weight, especially important for aerospace applications. Another advantage is that it benefits from redundancy because of the two separate powertrains. This is a major advantage for the
certification process [35]. However according to some regulations it is not allowed to have any extra
clutch. This means there can be no clutch between the electric motor and the gas turbine. This
would result in electric motor only mode not being possible and an extra loss in gas turbine only
mode when the battery is fully charged due to the extra drag in the electric motor [12]. However, the
author could find no evidence of such regulation in CS-25 or FAR-25 [36] [37]. Regardless, studies
have shown that even without a clutch this configuration still results in the least fuel consumption
and a highest efficiency for aircraft [12], although all studies performed so far have only been done
for light aircraft (< 1000 kg). The biggest drawback of this configuration is the increased complexity of the mechanical coupling [12] and the significant increase in control complexity [38] because
power flow has to be regulated and blended from two power sources.
In the most common control strategy (although mostly for electric cars) the gas turbine is almost
always on and operates at constant power output at its peak efficiency point [34]. The electric engine
is used when the power required is larger than the power delivered by the gas turbine (such as during
take-off). If the power needed for the propeller is less than the power delivered by the gas turbine
the remaining power can be used for charging the batteries by using the electric motor as generator.
Gas turbine
Power
converter
Electric
motor
Figure 2.4: Parallel hybrid architecture
The are other architectures such as the series-parallel hybrid and complex-hybrid architecture,
however they aren’t commonly used because of their inherent complexity. These types of architectures combine the advantages and disadvantages of both the series hybrid and parallel hybrid architectures. They are not suited for aerospace applications because they come with a severe weight
penalty when compared to the series - and parallel-hybrid configurations.
2.3.2. S ELECTED A RCHITECTURE
Ultimately, the most suited architecture for a hybrid electric regional aircraft is the parallel-hybrid
architecture. The versatility in operating modes, combined with the potential for the smallest weight
make this the better choice for aerospace applications. Whether this assessment is entirely correct is impossible to know at this stage, not enough design studies comparing both power plants
12
2. P ROJECT D ESCRIPTION
in aerospace applications (especially aircraft over 1000 kg) were performed to really get conclusive
evidence that one architecture is more optimal than the other. The level of technological progress
between now and 2035 also has a large impact on what configuration is more feasible. For example
the series-hybrid architecture requires a much more powerful electric motor which might not be
feasible if certain technological progress is not achieved (such as high temperature superconducting). The weight of a certain architecture also depends on many other factors such as the chosen
control strategy, type of mission, etc...
Figure 2.5 shows the chosen architecture with all relevant parameters and symbols. Since the
battery delivers direct current (DC) and the electric motor requires alternating current (AC), an inverter is needed between the battery and electric motor which transforms the power from DC to AC.
This inverter also greatly increases the voltage coming from the batteries. This is needed to reduce
the required thickness (weight) of the cables, see Section 3.7.
ηgasturb
Pfuel
Pgasturb
Gas turbine
Pshaft
PbatOffTake
Pbat
Electric
motor
Inverter
ηbat
ηelec
Pem
ηprop
ηEM
Figure 2.5: Architecture of the power plant
With the technological development of reliable, solid-state, high power-density, power-related
electronics it would be beneficial in the not-so-far future to move towards a "More Electric Aircraft
(MEA)" [39]. The MEA uses electrical power to replace the hydraulic, pneumatic and mechanical
power in order to optimize the performance and life cycle cost of the aircraft. It would make the
subsystems easier to maintain, more durable, lower in cost and higher in performance. An additional advantage is that no air off-take in the gas turbine is needed, which increases performance.
The downside is that it requires a highly reliable, fault tolerant electrical power system and programmable solid-state devices in order to have adequate load management, fault isolation and diagnostic health monitoring [39]. However, such systems are already needed for the hybrid-electric
propulsion system [40]. This would also minimize the increase in weight the MEA concept would
bring. It might thus be beneficial to use such a concept for a hybrid-electric aircraft.
2.4. C ONTROL S TRATEGIES
13
As can be seen in Figure 2.5 there is the factor P batO f f Take which represents the power that is
diverted from the battery to power other electrical systems (which would be relatively large when
using the MEA concept). However, for the designs considered here the MEA concept is not used
because that would go beyond the scope of the project as well as introduce additional difficulties
in terms of estimating the power and weight requirements such a concept would bring. For these
reasons all subsystems are sized using the same methods as for a conventional aircraft and the factor
P batO f f Take is zero for all designs.
2.4. C ONTROL S TRATEGIES
Deciding how and when to use the electric motor and/or gas turbine throughout the mission also
has a very large impact on the amount of batteries and fuel to be taken on board. Since there are two
power sources present, many different design variables are introduced which represent how much
of what power source is used at what time. In order to keep the number of design variables as low as
possible a new variable is introduced: the power split (S i ). This variable can vary between 0 and 1
during the entire mission with 0 representing the use of only the gas turbine and 1 representing the
use of only the electric motor at that specific point in time.
Si =
P emi
P sha f ti
(2.2)
For example a power split of 0.6 means that 60% of the power delivered to the propeller shaft comes
from the electric motor and the other 40 % from the gas turbine.
To reduce the complexity the power split is chosen to be constant for each mission phase apart
from the cruise phase. Since the cruise phase is much longer than other flight phases it is chosen
to make the power split variable during this phase. A certain power split has to be selected for the
beginning of the cruise phase, and one for the end of the cruise. During this flight phase the power
split will vary linearly between the two chosen power splits. During the descent no power split
is defined since not much power is required and the gas turbine usually idles during these flight
phases, for more information see Section 3.4.4. Whether there is an optimal power split for each
flight phase is a difficult question to answer. Intuitively one might think that it would be beneficial
to have a large power split (more gas turbine power than electrical power) in the beginning of the
mission in order to burn more fuel and get a lighter aircraft and later on use more electrical power
in order to reduce the total fuel burn. This effect is even magnified when using lithium-air batteries
since these gain weight during usage, thus it being more beneficial to use them as late in the mission
as possible. Whether this assessment is correct is investigated in Section 4.2.4.
Choosing a certain power split for each flight phase might not always be the most intuitive way
of choosing how hybrid an aircraft is. It is also very hard to specify a "good" power split before
anything about the design is known. For these reasons another control strategy is introduced. The
so-called "constant gas turbine power" operating mode. When using this operating mode a certain
(max-continuous) gas turbine power is chosen in stead of a power split. During take-off and climb
the maximum available gas turbine power is used and if needed supplemented with power from
the electric motor2 . During the cruise phase the gas turbine is used at its most fuel efficient power
setting3 and again the electric motor is used to provide the extra power that might be needed. The
benefit of this control strategy is that the gas turbine can generally be sized smaller compared to the
power split operating mode4 and is operated at a more efficient point resulting (in theory) in a more
optimal design which requires less fuel for the same mission. In theory it might be possible to select
2 When the power delivered by the gas turbine is less than the required shaft power
3 Smallest SFC
4 Dependent on the chosen power split
14
2. P ROJECT D ESCRIPTION
power splits such that the resulting design is exactly the same as for the constant gas turbine power
operating mode. In Section 4.2.3 the comparison is made between both operating modes.
An additional advantage of the constant gas turbine power control strategy is that if the required
shaft power is less than the delivered gas turbine power the excess power could be used for charging
the batteries during flight which could result in the aircraft landing with partially (or completely)
charged batteries, potentially reducing cost and turnaround time. In that case the electric motor is
used as a generator.
2.5. I MPORTANT PARAMETERS
Since many designs are generated using different operating modes, some parameters have to be
introduced which can be used to compare different designs. Also, a certain measure of how hybrid a certain design is has to be introduced. Most commonly used in literature are the degree of
hybridization for energy (HE ) and power (HP ) [41], defined as:
HP =
P emmax
P sha f tmax
and
HE =
E bat
E t ot
(2.3)
(2.4)
However, the degree of hybridization of power is not really a good parameter to measure how
hybrid a design is. For example having a large electric motor that is only used for a short while
will results in a large degree of hybridization of power while only a very small part of the mission is
"hybrid". In that regard the degree of hybridization of energy is a better parameter. However, it is
also not ideal since the specific energy of fuel is much larger compared to the battery specific energy,
and the efficiency of the electrical systems much higher than that of the gas turbine. This results in
values of HE being generally quite low (< 0.2) even though the total supplied electric motor energy
(E em ) might be higher than the total supplied gas turbine energy (E g ast ur b ). For this reason another
parameter is introduced: the supplied power ratio (Φ) [41]. This is defined as the total electric motor
power over the entire mission in relation to the total shaft power over the entire mission.
Φ=
E em t ot
E sha f t t ot
(2.5)
The advantage of this parameter is that it is more intuitive than the degree of hybridization of
energy. A value of Φ = 0 represents a conventional aircraft while a value of Φ = 1 represents a fully
electric aircraft. When using a constant power split over the entire mission the supplied power ratio
will be approximately the same as this constant power split.
3
M ETHODOLOGY
In this chapter the methodology for sizing the different components and ultimately leading to a certain design for a hybrid-electric aircraft is presented. This design process is completely automated
in the Initiator program [42]. That is why first a short description of the Initiator program is provided
in order to better understand the design process that is used. Later, the sizing of different components including the batteries and electric motor is explained. Next, a brief description is given of
the implementation of the methods into the Initiator. And lastly, the limitations of the presented
methodologies are given.
3.1. I NITIATOR
The Initiator is a (mostly) physics-based conceptual aircraft design program developed at the TUDelft. It is implemented in MATLAB [43] and allows for the generation of a preliminary aircraft
design based on a set of (basic) input parameters. Creating such a design takes about 20 minutes.
It is capable of generating very diverse aircraft designs, from conventional aircraft to three-surface
aircraft to blended wing bodies.
What makes this program ideal for the purpose of designing a hybrid-electric aircraft is twofold.
First of all, it is modular in nature which allows for the easy addition and modification of new modules and parts. Secondly, because generating a design takes a relatively short time, the influence of
changing certain input parameters on the design is easy to determine. This is especially useful in the
case of a hybrid-electric aircraft where the value of various input parameters (such as the expected
battery specific energy) can not be known for sure, and a certain range of values has to be examined.
To better understand the design process a short explanation is given of how the Initiator program works, as well as what kind of inputs are required. Figure 3.1 shows the basic structure of the
program. Keep in mind that this is a very simplified structure and many modules are omitted for
the sake of clarity and other modules are bundled together into one module. Nevertheless, it does
give a good overview of how the Initiator achieves a new design.
The input file contains the basic requirements the aircraft needs to achieve such as range, payload, passenger amount, etc. as well as some basic geometry parameters such as wing location
(low-, mid- or high wing) and tail type. This file is read in the beginning of the run and the values
remain constant during the entire design process. The settings file contains all other input parameters that are not present in the input file. This a an extensive list of hundreds of constants that are
used during the design process. Almost all modules use certain parameters from this settings file.
Section 3.10 contains a list of settings that are added to be able to achieve a hybrid-electric aircraft
design.
After the input file is read, a database of reference aircraft is used, together with a class 1 weight
estimation to achieve a first estimate of the basic aircraft parameters such as MTOM. Afterwards,
15
16
3. M ETHODOLOGY
Settings file
Input file
Reference
aircraft
database
Class 1
Weight
Estimation
Wing- and
power
loading
Geometry
design
modules
No
Class 2.5 weight estimation
Design
converged?
All modules
No
Class 2
Weight
Estimation
Yes
Design
Performance
Estimation
Modules
Yes
Converged?
Aerodynamic
analysis
modules
Mission
Analysis
Class 2
Weight
Estimation
Aerodynamic
analysis
modules
Mission
Analysis
Figure 3.1: Simplified flow chart showing the basic workings of the initiator program
based on requirements and regulations (FAR 25 or 23), a wing- and power loading diagram (in case
of turboprop aircraft) is constructed which results in a design point. Figure 3.2 shows an example of
such a diagram.
Next, geometry design modules are ran which estimate the basic components of the aircraft
such as the wing, fuselage, engines and control surfaces. Afterwards, a class 2 weight estimation is
preformed which estimates the mass of all components as well as sizes some components (landing
gear, fuel tanks,...) which were not sized in the geometry design modules.
When the weight estimation is completed, multiple aerodynamic analysis modules are run: AVL,
C L max estimation and parasite drag estimation. The aerodynamic forces determined by AVL are
also used to determine the wing weight. The next module that is used is the mission analysis module, this module determines the fuel (and battery) mass needed for the mission. It also runs AVL
again as part of the mission analysis in order to determine the drag polar.
Subsequently a class 2.5 weight estimation is performed. This weight estimation runs multiple
modules in a certain order. It uses inputs from the mission analysis, such as fuel and battery mass
to perform a more accurate class 2 weight estimation. Next, the aerodynamic analysis modules are
run again as well as another mission analysis. The class 2.5 weight estimation keeps running those
modules in that specific order until the difference in MTOM between 2 iterations is below a certain
margin.
Finally, after the class 2.5 weight estimation is converged, the performance estimation module
is run which evaluates the performance of the design, constructs a manoeuvre loading diagram and
payload-range diagram. When this is finished, the program starts the entire design loop again from
the wing- and power loading module until the difference between 2 subsequent iterations is below
a certain margin.
3.2. R EFERENCE A IRCRAFT D ESIGN
17
The aircraft geometry is defined in so called parts. Parts are objects such as the wings, landing
gear, fuselage, etc.. These objects not only store geometrical data of each part, but also other important parameters. These parts are a convenient way of keeping track of certain variables and passing
it between modules.
The Initiator program as explained above is only capable of designing aircraft which use turbofan engines. Many changes had to be made in order for it to design aircraft with turboprop engines,
not to mention hybrid-electric aircraft. Many modules had to be modified, what these modifications are will be explained in the next sections. Also new parts had to be added: batteries, electric
motor, wiring and inverter.
3.2. R EFERENCE A IRCRAFT D ESIGN
As mentioned previously, modifications have to be made to the initiator in order to make it possible
for the program to design a turboprop aircraft. This has to be done before additional modifications
can be applied which would allow the initiator to design a hybrid-electric aircraft. This section gives
a brief overview of the changes made to the initiator in order for it to be able to design a turboprop aircraft. However, since this is not the main focus of the project only the general changes are
explained and unnecessary details have been avoided.
In order to validate the changes made, a reference aircraft will be constructed based upon the
ATR 72-600. Later, in Section 4.1, this newly constructed reference aircraft is compared to the ATR
72-600 in terms of performance, mass, geometry and fuel burn.
3.2.1. E NGINE AND P ROPELLER S IZING
Since the initiator is only able to design aircraft with turbofan engines, the engine geometry sizing (and placement) module as well as the class 2 weight estimation (and subsequently class 2.5)
module need to be modified to able to cope with turboprop engines.
The geometry of the engines is determined based on the maximum power they have to deliver.
This maximum power is either determined using the power loading found from the power loading
diagram, see Figure 3.2, or from the mission analysis 1 , depending on how far the program is in the
design iteration. From the maximum power the length and diameter and mass of the gas turbine is
determined using respectively Equation 3.1, 3.2 and 3.3 derived by Raymer [44], based on empirical
data.
µ
d g ast ur b = 0.25 ∗
P g ast ur b
¶0.12
(3.1)
1000
µ
l g ast ur b = 0.12 ∗
P g ast ur b
¶0.373
(3.2)
1000
µ
m g ast ur b = 0.96 ∗
P g ast ur b
¶0.803
1000
(3.3)
The installed engine mass is equal to 1.3∗m g ast ur b . Other engine parts which are taken into account
are the engine controls, engine starter and nacelle, as well as the mass of the propeller. The propeller
diameter is based on the maximum propeller tip speed determined using Equation 3.4 derived by
Roskam [45]. Where M t i p is the maximum propeller tip Mach number, by default 0.8.
s
d pr op =
1 Taking into account the number of engines
a2
π2 ∗
f2
∗ (M t i p − M 2 )
(3.4)
18
3. M ETHODOLOGY
Since no propeller model is present in the Initiator program and implementing such a model
would be outside the scope of this project, some other method has to be used for determining the
propeller efficiency under multiple conditions. During the class 2 sizing process the propeller efficiency is assumed as a constant. This approach is not accurate enough during the mission analysis
since a large variation in the propeller efficiency exists during the entire mission. For this reason the
ideal propeller efficiency (Equation 3.5) is used during the Class 2.5 sizing process. Since this equation represent the maximum theoretically obtainable propeller efficiency, it is scaled with a factor
of 0.9 in order to achieve more realistic values.
2
η pr op i d eal =
1+
³
T
ρ
A d i sk ∗V 2 ∗ 2
+1
´1/2
Figure 3.2: Example of a power loading diagram of an aircraft comparable to the ATR72-600
(3.5)
3.2. R EFERENCE A IRCRAFT D ESIGN
19
3.2.2. G AS TURBINE POWER AND FUEL CONSUMPTION VARIATION
During any mission there is a large variation in velocity and altitude. Since the maximum power
and fuel consumption of a gas turbine are not constant with velocity and altitude, large variation
in SFC will occur during the flight. A model to calculate the variation of SFC and maximum thrust
for a turbofan engine is already implemented in the Initiator program. However, no such model is
present for turboprop engines. Implementing such a model from scratch would go far beyond the
scope of this project, however, assuming a constant maximum power and SFC would result in large
errors. Therefore, data was taken from the Fokker 50 engine (Pratt & Whitney PW125 2 ) [3] in order
to construct a model based on that data. Later on, this model can then be scaled with the engine
power (since the used maximum engine power is not necessary the same as for the PW125) to find
the maximum power and fuel consumption variation with speed and altitude. Since, depending
on the chosen operating mode, large variations in power setting can also occur (which can have a
very large effect on the SFC), the variation of SFC with power setting for the same engine is also
incorporated into the model.
Since data is only available for a velocity range between 130 KEAS (66.88 m/s) and 200 KEAS
(102.89 m/s) and an altitude range of 10000 ft (3048 m) to 30000 ft (9144 m), some inter- and extrapolation has to be performed. This is generally inadvisable since extrapolation can lead to large
errors, however, since during the mission the velocity and altitude lie mostly within the aforementioned range, any errors will not have a large influence on the final result. It is worth mentioning
that this model is not meant to be very accurate for all engines, but merely to give reasonable results
for SFC and power variation. That being said, it is expected that this model is more than adequate
for the purpose of this project.
Figure 3.3 shows the variation of maximum continuous power with altitude and velocity. There
is an upper limit to to maximum continuous power of around 1.6 MW for this particular engine.
This maximum power is later on scaled with the maximum power of the current design so that
the variation is exactly the same for all engines (but the maximum power differs). According to
aircraft performance theory, the equivalent shaft power of the turboprop at any given altitude may
be related to its sea-level value by the relationship
µ ¶n
P
ρ
=
P0
ρ0
(3.6)
where in the troposphere (up to an altitude of approximately 11 km) the exponent n has a value
of approximately 0.75 [46]. However, since the power has a certain maximum value at which the
maximum power curves become flat (at around 1.6 MW in figure 3.3) the above relationship is only
valid for the slope of the curve (i.e. as if there was no maximum value to the power), see Figure 3.4.
In this graph only the curve for a velocity of 250 knots (≈ 129 m/s)is shown, however the relation is
also valid for any other velocity.
For the fuel flow variation (see Figure 3.5) the upper limit of the fuel flow is not the same for all
velocities. For example for V = 300 kts the upper limit is approximately 123 g/s while for V = 200 kts
it is around 130 g/s. Dividing the fuel flow by the power (and doing some unit manipulation) yields
the SFC variation, see Figure 3.6. As can be seen, this graph does not always have the smoothest
curves. This is due to the inter- and extrapolation of both the fuel flow and the power variation
graphs. However, as mentioned before, it does give figures accurate enough for the purpose of this
project. It can be clearly seen that there is little variation in SFC with altitude, while a larger variation
exists for velocity.
The SFC not only varies with speed and altitude but also with power setting. Figure 3.7 shows
the variation of the SFC with powersetting for a typical cruise condition (V ≈ 103 m/s and h = 6096
m). For the sake of clarity only the values for power settings between 0.2 and 1 are shown since for
2 This engine is also used in the ATR72-600
20
3. M ETHODOLOGY
lower power settings the SFC increases rapidly. It is assumed the same variation holds for different
velocities and altitudes.
This model is implemented into the Initiator program by normalizing all values and scaling it
with the maximum power of the gas turbine. For the electric motor it is assumed there is no variation
in power or power consumption with altitude, velocity or power setting.
·106
Max. continous power [W]
1.8
V = 0 kts
V = 100 kts
V = 200 kts
V = 300 kts
1.6
1.4
1.2
1
0.8
0.6
0.4
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Altitude [m]
1
·104
Figure 3.3: Power variation as a function of velocity and altitude [3]
1.1
P
³P 0 ´n
1
ρ
ρ0
, n=0.75
³
´
ρ n
ρ0
[-]
0.9
0.8
0.7
0.6
0.5
0.4
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Altitude [m]
³ ´0.75
ρ
Figure 3.4: Slope of PP compared to the slope of ρ
for a velocity of 250 knots
0
0
0.8
0.9
1
·104
3.2. R EFERENCE A IRCRAFT D ESIGN
21
V = 0 kts
V = 100 kts
V = 200 kts
V = 300 kts
Fuel flow [g/s]
140
120
100
80
60
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Altitude [m]
0.9
1
·104
Figure 3.5: Fuel flow as a function of velocity and altitude [3]
V = 0 kts
V = 100 kts
V = 200 kts
V = 300 kts
340
g
SFC [ kW h ]
320
300
280
260
0
0.1
0.2
0.3
0.4
0.5
0.6
Altitude [m]
Figure 3.6: SFC as a function of velocity and altitude [3]
0.7
0.8
0.9
1
·104
22
3. M ETHODOLOGY
360
g
SFC [ kW h ]
340
320
300
280
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Power setting [-]
Figure 3.7: SFC variation with power setting for a typical cruise condition with V = 200 knots and h = 20000 ft (= 6096 m)
[3]
3.3. C LASS 2 B ATTERY AND F UEL S IZING
23
3.2.3. OTHER M ODIFICATIONS
Some other modifications also had to be made in order to be able to design a turboprop aircraft. For
example, at the end of each design iteration there is a check whether all the passengers fit into the
fuselage, if not, the fuselage length is increased. This was necessary because the Initiator program
often underestimates the fuselage length for regional aircraft.
Large changes are also made to the mission analysis modules which will not be expanded upon
here since the complete explanation of the mission analysis modules can be found in Section 3.4.
3.3. C LASS 2 B ATTERY AND F UEL S IZING
In this section, the methodologies are presented that are used to determine the amount of batteries
and fuel that have to be taken on board. As mentioned before, the Initiator program uses both a
class 2 and a class 2.5 weight estimation, in this section only a class 2 method is discussed, Section
3.4 contains the class 2.5 sizing process. The class 2 methods discussed here are based on many
assumptions and are not accurate in all cases. However, this is not a problem as the Initiator program only uses the Class 2 methods for determining the battery and fuel weight as a first guess, and
later on, the found values are overwritten by the values found in the class 2.5 sizing process (mission
analysis). As such, the accuracy of these methods only affects the time it takes for the program to
converge, and not the final design.
3.3.1. B ATTERY S IZING
Since there are two distinct operating modes implemented for hybrid-electric aircraft, the sizing
process will also differ for these two operating modes. First, the method used for class 2 sizing of the
batteries for the power split operating mode is presented and afterwards the methodology for the
constant gas turbine power operating mode.
P OWER S PLIT O PERATING M ODE
As mentioned before, a certain power split is defined for each phase of the mission. For estimating
the battery amount needed for the take-off and climb phase, the same method is used. First, the
amount of energy for those phases are estimated using the fuel fractions (of the non-hybrid aircraft).
For example for the climb phase:
m f uel cl i mb =
m pr ecr ui se
1/F F cl i mb − 1
(3.7)
From which the energy for the entire climb phase can be determined using the specific fuel consumption (SFC):
m f uel cl i mb ∗ 1000 ∗ 1000
E cl i mb =
(3.8)
SFC
Knowing the total energy that needs to be delivered by the engine, the battery energy can be
determined using the corresponding power split for each phase as well as the relevant efficiencies.
For example for the climb phase:
E batcl i mb =
E cl i mb ∗ S cl i mb
η el ec ∗ η em ∗ η bat
(3.9)
With η el ec being the efficiency of the wiring and inverter, η em the efficiency of the electric motor
and η bat the discharging efficiency of the battery. From the battery energy the battery mass is found
using the battery specific energy.
24
3. M ETHODOLOGY
For the cruise phase two different splits are defined: one at the beginning of the cruise phase
(S pr ecr ui se ) and one at end of the cruise phase (S end cr ui se ). From these splits an average split for the
entire mission is defined:
S av g =
S pr ecr ui se + S end cr ui se
2
(3.10)
This is valid because the power split changes linearly over the entire cruise phase. For the class
2 weight estimation, this average split (S av g ) is taken over the entire mission range, so not just the
cruise phase. Another assumption that is made is that D * V is constant during the cruise phase. This
is an assumption that in some cases might lead to errors, however, as mentioned before, this is not
really a problem since later on in the design iteration a more accurate method for determining the
battery mass is used which overrules the method here. Any inaccuracies in this method will result
in a longer convergence time, but will not affect the final design.
From these simplifications it follows that the power the electric motor (thus also the batteries)
have to deliver is constant for the entire cruise phase. This power of the electric motor is given by:
P em = D ∗ Vcr ui se ∗ S av g ∗
1
η pr op
(3.11)
From which the battery power can be determined, taking into account the efficiencies:
P bat =
P em
η el ec ∗ η em ∗ η bat
(3.12)
Since this power is constant over the entire cruise phase it can be multiplied by the time of the cruise
phase ( VcrRui se ) to find the total electrical energy needed for the entire cruise phase. From which,
using the battery specific energy and volumetric energy density, the battery weight and volume required for the cruise phase can be determined. It would also be possible to determine the battery
weight during the cruise phase by using the hybrid-electric range equation, which is discussed in
Section 3.3.2.
During the descent phase the electric motor is switched off, meaning the battery mass required
for this phase is always zero regardless of operating mode. After summing the battery mass and
volume required for each phase the total battery mass and volume is found. An extra 10% is added
to the battery mass and volume to have a buffer so the battery doesn’t discharge completely3 .
C ONSTANT G AS T URBINE P OWER O PERATING M ODE
Using this operating mode means that the power of the gas turbine is predefined and this engine
runs at its most efficient point during the majority of the mission. The rest of the power required is
delivered by the electric engine. No power splits are used during this operating mode, which means
the above method is not applicable for this operating mode. First of all, the energy required for each
flight phase (apart from cruise and descent) is determined using the same method as for the power
split operating mode (Equation 3.8).
The total take-off power is found from the power loading diagram, an example of which can be
seen in figure 3.2. Subsequently, the total take-off energy of the gas turbine can be determined using
the following relation:
E g ast ur b t akeo f f =
E t akeo f f ∗ P g ast ur b t akeo f f
P t akeo f f
From which the battery take-off energy (and mass) can be determined:
3 Which might result in damage to the battery pack
(3.13)
3.3. C LASS 2 B ATTERY AND F UEL S IZING
25
E bat t akeo f f =
E t akeo f f − E g ast ur b t akeo f f
η el ec ∗ η em ∗ η bat
(3.14)
For the climb phase the contribution of the gas turbine to the total energy can be known because
the required time-to-climb is known from the mission requirements. So the battery energy required
for the climb phase can be found:
E batcl i mb =
E cl i mb − P g ast ur bcl i mb ∗ t cl i mb
η el ec ∗ η bat ∗ η em
(3.15)
For this operating mode the gas turbine is run at its most efficient point during the cruise phase.
For the class 2 sizing, the SFC variation with power setting (Figure 3.7) is not known yet. For this
reason a certain constant power setting during cruise is selected by the designer. Using this power
setting, the power of the gas turbine (P g ast ur bcr ui se ) is determined and the power of the electric motor
is then given by:
P em =
D ∗ Vcr ui se
− P g ast ur bcr ui se
η pr op
(3.16)
From which the total energy of the battery can be determined using the same method as was
used for the power split operating mode (Equation 3.12 and beyond). Again, during the descent
phase the electric motor is turned off, so no battery mass is needed for that phase. The total battery
mass is determined by summing all the contributions of all the flight phases and adding a certain
buffer (by default 10 %).
L IMITATIONS
When using the constant power operating mode and selecting a gas turbine power, which is larger
than the power required during a certain flight phase, it results in a negative battery energy. In
reality this would mean the battery can be charged during the flight using the excess gas turbine
power. Implementing battery charging would require the program to keep track of the state-ofcharge during the mission to know when the batteries are full as well as when they are empty and
more battery needs to be added. This would require a more detailed mission analysis (class 2.5),
and as such is not implemented in the class 2 sizing of the batteries. When the battery energy found
is negative, zero battery mass is added instead of the batteries being charged. For this reason there
might be some errors when selecting a large power for the gas turbine.
When using Lithium-Air batteries the battery mass increases by approximately 0.000192 kg/Wh
during discharging, see Section 2.2.1. This again, is not implemented in the class 2 sizing of the
batteries.
The calculation of the battery mass needed during the cruise phase, is based upon the assumption that D * V is constant during cruise. This simplification may lead to errors and as such it would
be better to use the new hybrid-electric range equation discussed in the next section. However, at
the time of writing this is not implemented.
3.3.2. F UEL
A class 2 method for determining the fuel weight was already implemented into the Initiator. This
method is modified to be able to deal with hybrid-electric aircraft.
For the power split operating mode, the fuel weight for the take-off and climb phase is determined by scaling the fuel fractions with their respective power split. For the constant power operating mode, the fuel needed for take-off and climb is found from the total gas turbine energy needed
during each phase. For the take-off phase Equation 3.13 is used. While for the climb phase, the gas
turbine power is multiplied with the time-to-climb:
26
3. M ETHODOLOGY
E g ast ur bcl i mb = P g ast ur bcl i mb ∗ t cl i mb
(3.17)
The fuel weight is subsequently determined from the gas turbine energy as follows:
m f uel =
SFC ∗
E g ast ur b
1000
(3.18)
1000
For the descent phase the fuel fraction is used for both operating modes since there is no difference in control strategy for each operating mode during this phase. The fuel fraction is not scaled
since no electric motor power is used during the descent.
The fuel weight during the cruise phase for an ordinary turboprop aircraft is determined using
the Brequet range equation:
¶
µ
m pr ecr ui se
1000 ∗ 1000 L
R = η pr op
(3.19)
ln
SFC
D
m end cr ui se
From the above equation the fuel weight can be found since the range is known as well as m pr ecr ui se .
However, this equation is not valid for hybrid-electric aircraft since not only fuel is used as energy
but also batteries (of which the weight at end of the cruise phase is not lower than at the beginning).
As such, a new equation has to be derived which is also valid for hybrid-electric aircraft. This new
hybrid-electric range equation is:
R=
1
S
η el
+ (1 − S) ∗ SFC ∗ e f uel
∗
µ
¶
e combi ned ∗ E pr ecr ui sse + m empt y
CL
1
∗ η pr op ∗
∗ln
CD
e combi ned
m empt y
(3.20)
With η el being the total electrical efficiency from the battery to the electric motor output:
η el = η bat ∗ et a el ec ∗ η em
(3.21)
The factor e combi ned is the combined specific energy of both the batteries and the fuel and is defined
as:
e combi ned =
x ∗ e f uel + (1 − x) ∗ e bat
e f uel ∗ e bat
(3.22)
Where ’x’ is:
x=
S
E bat
=
E t ot
S + (1 − S) ∗ SFC ∗ e f uel ∗ η el
(3.23)
The derivation of this equation can be found in Appendix A. This equation is only valid for a
constant power split (S). As such, if the power split varies during the cruise phase, the average power
split is used. Also, a constant SFC is assumed, as well as a constant propeller efficiency and CCDL . Using
this equation, for a given range and power split, the required energy (E pr ecr ui se ) can be found. From
this energy the battery and fuel weight can be calculated as follows:
m bat =
m f uel =
E pr ecr ui se ∗ x
e bat
E pr ecr ui se ∗ (1 − x)
e f uel
(3.24)
(3.25)
For a conventional aircraft (S=0), the results of Equation 3.20 will correspond exactly to the original Brequet range equation. Figure 3.8 shows the results of this equation for a variable power split
and a range of 1528 km, as well as the following inputs:
3.3. C LASS 2 B ATTERY AND F UEL S IZING
27
• SFC = 300
[g/kWh]
• e bat = 1000
[Wh/kg]
• e f uel = 12778
[Wh/kg]
• η el = 0.95
[-]
• η pr op = 0.8
[-]
•
CL
CD
= 20
[-]
• m empt y = 15000
[kg]
For the above set of inputs, the fuel and battery weight varies almost linearly with power split.
Figure 3.8 is constructed using a constant empty mass, in reality the empty mass will increase with
an increasing power split since the total aircraft mass increases and as such also the structural mass.
In the next chapter this is discussed in more detail.
1,800
Fuel Weight
Battery Weight
1,600
1,400
Mass [kg]
1,200
1,000
800
600
400
200
0
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Power Split [-]
Figure 3.8: Results of the adapted Brequet range equation for a variable fuel weight and power split
For the constant power operating mode the approach described above is not used. Since the gas
turbine power during the cruise phase is known, this power is multiplied with the cruise time to find
the fuel weight..
28
3. M ETHODOLOGY
3.4. C LASS 2.5 B ATTERY AND F UEL S IZING
The class 2.5 method for determining the fuel and battery weight, as well as the maximum power
that the electric motor and gas turbine have to deliver, involves performing a mission analysis. This
mission analysis performs an analysis of each flight phase and determines all relevant parameters
at each time step. This time step varies for each mission segment. For example, during the cruise
phase a longer time step is taken than during take-off or landing since the parameters during cruise
will not change much from one time step to the next.
Below all the mission segments are listed, and in Figure 3.9 an example of a typical mission profile
is shown. Although the take-off and landing phase are present in this mission profile, they can not
be seen in the figure since the duration of those segments is very short.
1. Standard Mission
• Take off
• Climb 1
• Cruise 1
• Descent 1
• Landing 1
2. Extended Mission
• Climb 2
• Cruise 2
• Descent 2
• Hold/Loiter
• Descent 3
• Landing 2
altitude (m)
Loiter
Descent 3
Descent 2
Cruise 2
1
Cruise 1
Climb 2
1.2
Descent 1
·104
Climb 1
1.4
0.8
0.6
0.4
0.2
0
0
200
400
600
800
1,000 1,200 1,400 1,600 1,800 2,000 2,200 2,400
range (m)
Figure 3.9: Example of a typical mission profile that can be used to determine the battery and fuel weight
3.4. C LASS 2.5 B ATTERY AND F UEL S IZING
29
For the Class 2.5 sizing, the extended mission is used since enough fuel/batteries have to be
taken on board to abort the landing, divert to another airport as well as loiter at that airport for
some time (30 minutes).
In this section the mission analysis for each flight segment is explained. Some segments (such as
descent) occur multiple times during one (extended) mission. Although for each of these segments
different inputs are given, the implementation of each repeated segment is identical and as such
are only explained once. The focus of this section lies on the changes made to the mission analysis
module. That being said, a short description of the workings of the original module is also given in
order to better understand the modifications that are made.
The activity diagram of the flight phases the mission simulation goes through is shown in Figure
3.10. The simulation consists of an iteration loop, which starts by setting the initial conditions of
the state matrix (S). The state matrix stores the state of all the variables being tracked at each point
in time. It is also handed from each flight phase to the next to keep track of the state of the aircraft.
Table 3.1 shows the variable the state matrix handles. Many other variables such as the propeller efficiency are also included in the state matrix yet not shown in the table, since they are only included
to be able to plot them.
Table 3.1: Parameters the state matrix ’S’ keeps track of
Parameter
t
h
R
V
m f uel
m bat
E bat
γ
P em
P g ast ur b
P sha f t
T
D
Description
Time that has passed up until that certain point in the
mission
Altitude
Distance travelled up until
that point in the mission
Airspeed
Fuel burned up to that point
in the mission
Battery mass used up until
that point in the mission
Battery energy used up until
that point in the mission
Flight path angle
Electric motor power
Gas turbine power
Shaft power
Thrust
Drag
Unit
sec
m
m
m/s
kg
kg
kg
deg
W
W
W
N
N
All the initial conditions are set to 0, except for the aircraft weight, which is set to the MTOM. The
simulation then passes the state matrix to the first flight phase, the take-off, which in turn passes it
to the next phase, after the conditions to end of the respective phase are met. The diversion starts
with an alternate climb, which continues on with the state matrix from the descent, as a go-around
is performed. The diversion is only simulated if the "extendedmission" input is set to 1, which is the
case during the Class 2.5 sizing process. The fuel burn and battery weight calculated at the end of
the simulation is fed back to determine the new MTOM. The iteration loop runs until the calculated
fuel and battery mass are the same as the input fuel and battery mass within a certain margin. To
speed up this process, the variables W f br est and R r est have been created. These variables track the
30
3. M ETHODOLOGY
fuel burn and range from the end of cruise to the landing, and are fed back into the cruise phase. In
this way the descent can be started at the correct point in time to reach the required range or fuel
burn at the end of the landing. The same can not be done for the battery weight since the battery
weight does not decrease during the flight, it actually increases (if using lithium-air batteries). For
the mission analysis the batteries are treated as being part of the empty weight and the increase in
battery mass counteracts the decrease in fuel mass during flight.
This entire process was originally only implemented for non-hybrid aircraft with turbofan engines. The mission analysis module is first modified in order for it to be able to determine the fuel
weight for turboprop aircraft. In practice this meant completely rewriting the each flight phase
module such that there are two versions of each. One that is used in case turbofan engines are used
and one for when turboprop engines are used. Here only the version used for turboprop aircraft is
discussed with the modifications made for hybrid-electric aircraft.
3.4. C LASS 2.5 B ATTERY AND F UEL S IZING
31
Start
Set initial
conditions of state
matrix S
Take-off
Climb 2
Climb 1
Cruise 2
Extended
cruise time?
Yes
No
Descent 2
Descent 1
Loiter
Cruise 1
Yes
Descent 3
Extended Cruise
Extended
mission?
No
Calculate diversion
Rrest, Wfbrest
Landing 2
Landing 1
Calculate total fuel
burn and battery
weight
No
Fuel weight
converged?
Yes
End
Figure 3.10: Activity diagram of the flight phases of the Mission Analysis module
Calculate Rrest,
Wfbrest
32
3. M ETHODOLOGY
3.4.1. TAKE - OFF
Figure 3.12 shows the flow diagram of how the take-off phase is calculated. First the initial state
matrix (S) is loaded. This is 0 for all parameters apart from the weight, which is the MTOM. All
settings that are needed for this phase are loaded as well, these include constants such as the landing
gear drag increase and efficiencies of the battery, electric motor, etc..
Next, the take-off power is determined from the power loading diagram (see Figure 3.2 for an
example). This is the shaft power and is assumed constant for the entire take-off phase since this
is only a short flight phase with little variation in altitude. A power setting is also selected. The
power setting is 1 for the entire take-off phase, regardless of operating mode. Although this is not
the most efficient operating point, a power setting of 1 is also taken for the constant gas turbine
power operating mode. This is because choosing a lower power setting with a lower specific fuel
consumption will result in a much heavier electric motor since during the take-off (and climb) phase
the power requirement is generally the maximum of the entire mission. On top of that, the increase
in fuel mass will be almost negligible because there is only a slight increase in SFC, while the take-off
phase has a relatively short duration.
Next, the propeller efficiency has to be determined. However, as mentioned before, no propeller
model is currently implemented in the Intitiator, and implementing such a model would go beyond
the scope of the project, especially for contra-rotating propellers (as would be used on the designed
hybrid aircraft). For this reason it was chosen to use the ideal propeller efficiency and scale it with a
factor of 0.9.
As can be seen in Equation 3.5 determining the propeller efficiency requires that the thrust is
known, but the thrust also depends on the propulsive efficiency. So for the very first time step this
becomes a problem, and the thrust is determined using the static thrust equation 3.26 [46].
Ã
T st at i c = P t akeo f f 2/3 ∗ 4 ∗ ρ ∗ π ∗
µ
D pr op
2
¶2 !1/3
(3.26)
Even if this equation does not result in an accurate thrust value it will have a negligible effect on the
design since it is only used for the first time step (0.1 sec) after which Equation 3.32 is used.
From the C L and C D relation during take-off the lift and drag at the time step are determined,
the ground effect as well as the drag increase because of the landing gear are taken into account. If
during the current time step the aircraft is still on the ground an extra drag component is also added:
the ground friction drag (D g ).
Next, some derivatives of the state matrix are calculated, namely the change in flight path angle
dγ
dh
dR
( d t ), the change in pitch angle ( dd θt ), the change in speed ( dV
d t ), height ( d t ) and range ( d t ). These are
calculated using the lift, drag, weight, speed and flight path angles at the current time step. Using
the relations found in Section 3.2 the specific fuel consumption is determined based on the current
speed, altitude and power setting. The SFC is the same regardless of operating mode since the power
setting for both operating modes is the same. Until this point there is no difference in calculations
for both operating modes, however, now a differentiation is made. First the power split operating
mode is discussed.
Since the shaft power (P sha f t ) is known (equal to p t akeo f f ), the power the electric motor has to
deliver (P em ) can easily be found according to Equation 3.27.
P em = P sha f t ∗ S t akeo f f
(3.27)
With S t akeo f f being the power split during the take-off phase, not to be confused with state
matrix ’S’. With P em known, the power the batteries have to deliver (P bat ) is found using the relevant
efficiencies (See Equation 3.12). The power of the gas turbine (P g ast ur b ) is found in an analogous
d m bat
way as P em . From their respective power, change in battery energy ( d Edbat
t ) and mass ( d t ) as well
as the change in fuel mass the change in fuel weight per time step can be found:
3.4. C LASS 2.5 B ATTERY AND F UEL S IZING
33
d E bat
P bat
=
dt
3600
(3.28)
d E bat
d m bat
= dt
dt
e bat
d m f uel
(3.29)
SFC ∗ P g ast ur b
(3.30)
dt
1000 ∗ 1000 ∗ 3600
For the constant power operating mode the same parameters are determined using a slightly
different method. As per the definition of this operating mode P g ast ur b is constant. Since the power
that is input is not the take-off power but the maximum continuous power, P g ast ur b during the take=
off phase has to be scaled with the maximum continuous power setting. After which
determined using Equation 3.30 and P em can be found by:
P em = P sha f t − P g ast ur b
d m f uel
dt
can be
(3.31)
From which the battery energy and mass can be found using Equations 3.28 and 3.29. Using this
operating mode adds one extra complication. It is possible that during a flight phase the selected gas
turbine power is larger than the required shaft power. If that is the case the batteries can be charged
d m bat
using the excess power and d Edbat
> 0) is only done when the
t < 0. So adding battery mass ( d t
battery energy is larger or equal to the maximum battery energy needed so far during the mission
(i.e. when there is no more battery energy left from the already present battery mass) and d Edbat
t is
positive.
Subsequently, the total change in aircraft weight is determined, taking into account the decrease
in fuel weight and the increase in battery weight (when using lithium-air batteries). The emissions
the aircraft produces during the time step are also calculated. These emissions are CO 2 , H2O and
NO X and are determined taking into account the fuel burned as well as the altitude of the aircraft.
Lastly, the new state matrix is calculated using the derivatives calculated during the iteration
loop. If the screen height is reached (end of take-off) the iteration stops and the program moves
on to the next flight phase: climb. If the screen height is not yet reached, a new thrust is calculated
using Equation 3.32 and a new iteration at the next time step is started.
T t akeo f f =
P t akeo f f ∗ η pr op
(3.32)
V
During the take-off phase each time step is only 0.1 seconds because large changes in the aircraft
state occur in a relatively short time. Figure 3.11 shows the result of this iteration in terms of aircraft
altitude, speed and flight path angle for an arbitrary aircraft with the same requirements of the ATR
72-600.
3. M ETHODOLOGY
γ (deg)
speed (m/s)
altitude (m)
34
15
10
5
0
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
60
40
20
0
10
8
6
4
2
0
range (km)
Figure 3.11: Altitude, speed and flight path angle of an arbitrary hybrid-electric aircraft during take-off
3.4. C LASS 2.5 B ATTERY AND F UEL S IZING
Initial aircraft
state
Relevant
settings
Calculate
new thrust
35
Determine
take-off
power
Select power
setting (1)
Calculate
static thrust
Calculate
propeller
efficiency
Calculate lift
and drag
Aircraft on
ground?
No
Constant power
operating mode?
Calculate
SFC
Determine
derivatives
Calculate Pem, Pbat
based on selected
Pgasturb
Battery not
charging and
battery energy
depleted
Yes
Calculate
ground
friction drag
No
Calculate Pem, Pbat,
Pgasturb based on
the power split
No
Yes
No
Yes
End
Yes
Screen height
reached?
Determine change
in battery and fuel
energy and weight
Determine change
in battery energy
and mass
Determine change
in fuel weight
Calculate
new state
matrix
Calculate
emissions
Figure 3.12: Flow chart of the take-off phase
Determine change
in battery energy,
no change in
battery mass
Determine
change in
aircraft
weight
36
3. M ETHODOLOGY
3.4.2. C LIMB
The flow chart of the climb phase is shown in Figure 3.15. First, the maximum gas turbine power
at sea level (and V =0) is determined (take-off power). Next, an iteration time step is chosen. When
the aircraft has an altitude of under 200 meter the time step is 0.1 seconds, afterwards a time step
of 1 second is used until an altitude of 3048 meter (10000 feet) is reached after which the time step
increases again to 5 seconds. Using this method increases the step size whenever a relatively steady
state has been reached in order to reduce computation time.
Next, the drag polar is loaded (previously determined using AVL) and recalculated every few
minutes based on the shift in center of gravity due to fuel burn and battery mass increase. The
propeller efficiency is determined again using the ideal propeller efficiency equation (Equation 3.5)
from which subsequently the thrust can be determined (Equation 3.32).
The lift and drag are then calculated using the aircraft weight, thrust speed, flight path angle,
drag polar, etc.. The increase in lift and drag from the take-off flap configuration (up to an altitude
of 3000 feet) is also taken into account. The derivatives for speed, flight path angle, altitude and
distance can then be determined using the thrust, drag, lift, γ, speed and weight, as well as factors
such as the percentage of excess power that is used for climbing vs. accelerating to cruise speed. The
exact strategy of when to climb and when to accelerate will not be expanded upon further because
it is of little relevance to the project and was already implemented in the original Initiator program.
For the calculation of battery mass and fuel burn (as well as gas turbine power (P g ast ur b ) and
electric motor power (P em )) a differentiation is again made between the constant power operating
mode and the power split operating mode.
First the power split operating mode is discussed. The shaft power is assumed equal to the takeoff power (potentially scaled with a certain factor if maximum power is not required for climb). The
gas turbine power is then determined using the power split during the climb phase. If the requested
gas turbine power is larger than the maximum gas turbine power (based on speed and altitude) the
gas turbine power is taken to be equal to the maximum gas turbine power. If the same power split is
selected for take-off and climb this is the case almost immediately, resulting in the selected power
split being valid only for the first time step, as can be seen in Figure 3.13. The slight dip in gas turbine
power in the beginning of the climb phase is due to inaccuracies in the maximum gas turbine power
model (Section 3.2.2), however, such anomalies are expected to have negligible effect on the overall
design.
The electric motor power does not vary with speed and altitude, and as such can be taken constant for the entire climb phase. The shaft power is than determined as the sum of the P g ast ur b and
P em . With P g ast ur b as well as P g ast ur bmax known, the power setting is determined (1 for the case in
Figure 3.13). The SFC is subsequently calculated based on the power setting, speed and altitude,
while the change in battery mass is determined from P bat .
For the constant power operating mode, first a power setting is chosen (1 appears to be the best
choice for the same reasons as were discussed in the previous section). Then, based on the power
setting, the maximum gas turbine power, altitude and speed, the gas turbine power is determined
as well as the SFC. Next, after checking whether or not the battery energy is depleted, the change
in battery energy and mass is calculated. Now the change in fuel and aircraft weight is again determined. Subsequently the state matrix is calculated and a new iteration is started until the required
cruise altitude and mach number is reached.
Figure 3.14 shows the state of the aircraft during the climb phase. The peak that can be seen in
the flight path angle is due to the derivative of a certain state that can momentarily become very
large when a sudden change in state occurs (in this case when the aircraft stops accelerating and
only climbs). However, peaks like that only occur for 1 time step and as such will have a negligible
effect on the overall results, although, as a result, a slight dip in aircraft velocity can be seen in Figure
3.14.
3.4. C LASS 2.5 B ATTERY AND F UEL S IZING
4
37
·106
Shaft Power
Electric Motor Power
Gas Turbine Power
3.5
Power [W]
3
2.5
2
1.5
1
0
20
40
60
80
100
120
140
160
Range [km]
γ (deg)
speed (m/s)
altitude (m)
Figure 3.13: Graph of the shaft power, gas turbine power and electric motor power during the climb phase with a power
split of 0.5
1
0.8
0.6
0.4
0.2
0
·104
0
20
40
60
80
100
120
140
160
0
20
40
60
80
100
120
140
160
0
20
40
60
80
100
120
140
160
140
120
100
80
60
20
15
10
5
0
range (km)
Figure 3.14: Altitude, speed and flight path angle of an arbitrary hybrid-electric aircraft during the climb phase
38
3. M ETHODOLOGY
Aircraft state
at end take-off
Determine
maximum
power (takeoff power)
Relevant
settings
Select
iteration
time step
Determine
drag polar
Scale max gas
turbine power
based on altitude
and speed
Determine Pgasturb
based on power
split
No
No
Pgasturb
more than max
turboprop
power?
Calculate
propeller
efficiency
No
Calculate
thrust
Constant power
operating mode?
Calculate lift
and drag
Determine
derivatives
Yes
Determine power
setting
Select power setting
Scale max gas
turbine power
based on altitude
and speed
Pgasturb is maximum
gas turbine power
Calculate SFC
Determine Pgasturb
Calculate SFC
Cruise altitude
and speed
reached?
Determine Pem and
Pbat
Yes
End
Yes
Calculate
new state
matrix
Determine change
in battery energy
and weight
Determine Pem and
Pbat
Yes
Battery not
charging and
battery energy
depleted?
No
Calculate
emissions
Determine change
in fuel weight
Determine
change in
aircraft
weight
Figure 3.15: Flow chart of the climb phase
Determine change
in battery energy
and mass
Determine change
in battery energy,
no change in
battery mass
3.4. C LASS 2.5 B ATTERY AND F UEL S IZING
39
3.4.3. C RUISE
Firstly, before the cruise phase iteration is started, the drag polar is loaded (constructed using AVL).
Also, if using the constant power operating mode, a power setting is chosen that results in the lowest
SFC. In the current SFC model this will result in a power setting of around 0.885 for the entire cruise
phase. This search for the lowest SFC can be done outside the iteration loop because the variation
of SFC with power setting is assumed constant for the entire cruise phase in accordance with Figure
3.7.
Once the iteration is started, the drag polar is retrimmed based on the fuel burned (and the
battery mass increase in case of lithium-air batteries). Next, the lift drag and thrust are determined,
after which the propeller efficiency as well as the aircraft state derivatives can be calculated. These
derivatives depends on the cruise strategy that is chosen. There are 3 different strategies possible:
• Cruise climb
The aircraft climbs during the cruise phase as more fuel is burned. For the case of hybridelectric aircraft,a cruise descent can take place if the increase in battery mass (due to the
lithium-air batteries) is more than the decrease in fuel mass.
• Step climb
Similar to cruise climb, but the change in altitude occurs is steps with a certain interval.
• Constant altitude
As the name suggest, there is no change in altitude during the cruise phase and also, no
change in velocity.
For all the designs and results shown in this thesis the cruise climb strategy is used since this is the
most common strategy. The shaft power is determined using:
P sha f t =
T ∗V
η pr op
(3.33)
So for the cruise phase the thrust is calculated first, and afterwards the shaft power while for
all other flight phases (except hold/loiter) this is done the other way around. For the power split
operating mode the electric motor power (P em ), battery power (P bat ), power setting and the change
in battery and fuel weight are calculated using a very similar method as was employed for the climb
phase. The only difference is that for the cruise phase the power split is not constant. The user can
select a power split for the beginning and the end of the cruise phase and the split will vary linearly
during the entire flight phase. As a result, the derivative of the power split during cruise also has to
be calculated.
For the constant gas turbine power operating mode, the power setting has already been determined before the iteration started. After the maximum gas turbine power is calculated, the power
setting is used to determine P g ast ur b . From there on out P em , P bat as well as the SFC 4 can be calculated using the same method as was used for the climb phase. The change in battery energy and
mass is also determined using the same method as before, taking into account whether the battery
is being charged or not.
Next, the change in fuel weight and subsequently aircraft weight is determined as well as the
emissions. The new state matrix is calculated using the previously determined derivatives and the
iteration is started all over again until the required range is reached. It is also possible to run the
mission analysis with a certain fuel mass as input and the range will be calculated. In that case the
iteration runs until a certain amount of fuel is burned 5 .
4 The calculation for the SFC can be moved outside the iteration for an increase in computational speed as the cost of a
very slight decrease in accuracy since there is little variation in speed and altitude during the cruise phase and the power
setting is constant.
5 This mode has not been tested for hybrid-electric aircraft
40
3. M ETHODOLOGY
speed (m/s)
altitude (m)
Again, figure 3.16 shows the state of an arbitrary hybrid-electric aircraft during the cruise phase.
As is expected the flight path angle and velocity is almost constant while the altitude gradually increases.
7,800
7,700
7,600
7,500
140
139.8
139.6
139.4
139.2
139
γ (deg)
1
0
100
200
300
400
500
600
700
800
900 1,000 1,100 1,200 1,300 1,400
0
100
·10−2
200
300
400
500
600
700
800
900 1,000 1,100 1,200 1,300 1,400
0
200
300
400
500
600
700
800
900 1,000 1,100 1,200 1,300 1,400
0.5
0
−0.5
100
range (km)
Figure 3.16: Altitude, speed and flight path angle of an arbitrary hybrid-electric aircraft during the cruise phase
3.4. C LASS 2.5 B ATTERY AND F UEL S IZING
Aircraft state
at end take-off
Determine
drag polar
Relevant
settings
Constant power
operating mode?
41
Yes
Determine
power
setting for
minimal SFC
No
Retrim drag
polar
Scale max gas
turbine power
based on altitude
and speed
Determine Pgasturb
based on power
split
Calculate
lift, drag and
thrust
No
Calculate
propeller
efficiency
Constant power
operating mode?
Determine
derivatives
Determine
Pshaft
No
No
End
Yes
Yes
Pgasturb
more than max
turboprop
power?
Determine power
setting
Calculate SFC
Pgasturb is max gas
turbine power
Calculate SFC
Scale max gas
turbine power
based on altitude
and speed
Range reached?
Determine Pem and
Pbat
Determine Pgasturb
Calculate
new state
matrix
Determine change
in battery energy
and weight
Determine Pem and
Pbat
Calculate
emissions
Determine
derivative of power
split
Battery not
charging and
battery energy
depleted?
No
Yes
Determine
change in
aircraft
weight
Figure 3.17: Flow chart of the cruise phase
Determine change
in fuel weight
Determine change
in battery energy
and mass
Determine change
in battery energy,
no change in
battery mass
42
3. M ETHODOLOGY
3.4.4. D ESCENT
As mentioned before, for the descent phase, no power split is used. The gas turbine produces idle
power. The idle power is defined as a certain percentage of the maximum power. So for a smaller gas
turbine the idle power will be small compared to a larger gas turbine. At the same time, the power
of the electric motor during this flight phase is always zero (the electric motor is turned off). The
reason for this is that an electric motor can instantly deliver power when requested and does not
need to spool up. Since a gas turbine does need to spool up this engine is left on for safety reasons.
Should the maximum power of the electric motor be relatively large compared to the maximum
power of the gas turbine it would in theory be possible to switch the gas turbine completely off
during descent and use the power of the electric motor when, for some emergency, more power is
required. The gas turbine could then be spooled up while the electric motor is already providing
adequate power to climb again. However, at this time, no regulations exist for such a case, thus the
gas turbine idles during the entire descent. It might also be possible to use the idle power to charge
the batteries. Finding out exactly what the best and safest descent strategy is for a hybrid-electric
aircraft could be a subject of a further study.
Because of the chosen control strategy, there is no difference in fuel and battery calculation
during this phase for any operating mode. Figure 3.19 shows the flow chart of how the Initiator
determines the battery and fuel weight during this phase.
First, before the iteration is started, the power setting is selected. In this case this is the idle
power setting 6 . Next, like in the climb phase, an iteration time step is selected. By default this is 5
seconds, but it reduces to 1 second once an altitude of 607 meter 7 is reached since in this part the
descent is more dynamic and a better accuracy is required.
Based on the current altitude and speed the maximum gas turbine power is determined, from
which, using the power setting, the idle power (P i d l e ) is found. With the power known, the thrust
can be calculated from which again the propeller efficiency can be known. Subsequently the lift,
drag and the derivatives of the state matrix are determined.
The specific fuel consumption during the descent phase will be very high because running the
gas turbine at idle is not very efficient. However, since the power is so low, the overall fuel consumption is also relatively low. Since the electric power is not used, P em = 0 and P g ast ur b = P i d l e .
From these values the change in battery and fuel weight is determined as well as the new state of
the aircraft. Once the required altitude is reached, the iteration stops and the next phase is started.
Figure 3.18 shows the state of an arbitrary hybrid-electric aircraft during the descent. Again, as
is the case during the climb phase, the peak in the flight path angle is due to a sudden change in
state of the aircraft, resulting in a very large value for certain derivatives for one time step.
6 This is a setting that can be changed, by default the value is 0.02.
7 2000 feet
γ (deg)
speed (m/s)
altitude (m)
3.4. C LASS 2.5 B ATTERY AND F UEL S IZING
·104
1
0.8
0.6
0.4
0.2
0
1,360
140
120
100
80
60
1,360
0
43
1,380
1,400
1,420
1,440
1,460
1,480
1,500
1,520
1,540
1,380
1,400
1,420
1,440
1,460
1,480
1,500
1,520
1,540
1,380
1,400
1,420
1,440
1,460
1,480
1,500
1,520
1,540
−5
−10
−15
1,360
range (km)
Figure 3.18: Altitude, speed and flight path angle of an arbitrary hybrid-electric aircraft during the descent phase
Aircraft state
at end cruise
Power setting = idle
Relevant
settings
Select iteration time
step
Scale maximum
Pgasturb based on
altitude and speed
Determine Pidle
Calculate thrust
Calculate SFC
Determine
derivatives
Calculate lift and
drag
Calculate propeller
efficiency
Determine Pgasturb
(= Pidle)
Determine Pem and
Pbat (= 0)
Determine change
in fuel weight (no
change in battery
weight)
Determine change
in aircraft weight
Descent altitude
reached?
Calculate new state
matrix
Calculate emissions
No
Yes
End
Figure 3.19: Flow chart of the descent phase
44
3. M ETHODOLOGY
3.4.5. L ANDING
speed (m/s)
altitude (m)
Figure 3.21 shows the flow chart of how the landing phase is calculated. Before the iteration is
started, the landing drag polar is determined. The effect of the high lift devices is also taken into
account. Next, as in all the other flight phases, the propeller efficiency is determined and afterwards the lift and drag is calculated. Again, the effect of the landing gear and high lift devices is
taken into account as well as the ground effect when below a certain altitude ( hb < 0.1). Afterwards,
a check is made whether the aircraft is on the ground or not. If so, the ground friction drag (based
on the brake coefficient) as well as the reverse thrust (if applicable) is added to the total drag. Afterwards, the derivatives are determined based on the previously calculated parameters, as well as the
state and location of the aircraft. The thrust and shaft power are determined next, also dependent
on whether the aircraft is on the ground or not (reverse thrust or idle thrust).
When using the power split operating mode, the gas turbine power is determined using the
input power split for the landing phase. From which all other remaining parameters are determined
using a similar method as was previously discussed. For the constant gas turbine power operating
mode, it is chosen to only use the gas turbine power for the landing phase, apart from when the
required power would be more than the maximum gas turbine power 8 . As such, no charging of the
batteries will occur during this flight phase. One could also choose to use the gas turbine power
differently during this flight phase, however, as this phase is extremely short compared to the other
flight phases (apart from the take-off phase), any change in control strategy for the landing phase
will have negligible effect on the overall battery and fuel weight.
Figure 3.20 shows the state of an arbitrary hybrid-electric aircraft during this flight phase, as can
be seen, no flare is present. The aircraft descents at constant velocity until the altitude is zero, after
which it will brake and slow down.
15
10
5
0
1,527.2 1,527.3 1,527.4 1,527.5 1,527.6 1,527.7 1,527.8 1,527.9
1,528
1,528.1
1,527.2 1,527.3 1,527.4 1,527.5 1,527.6 1,527.7 1,527.8 1,527.9
1,528
1,528.1
1,527.2 1,527.3 1,527.4 1,527.5 1,527.6 1,527.7 1,527.8 1,527.9
1,528
1,528.1
60
40
20
0
γ (deg)
0
−1
−2
−3
range (km)
Figure 3.20: Altitude, speed and flight path angle of an arbitrary hybrid-electric aircraft during landing
8 This is almost never the case except when choosing a very small gas turbine power.
3.4. C LASS 2.5 B ATTERY AND F UEL S IZING
Aircraft state
at end take-off
45
Determine
landing drag
polar
Relevant
settings
Calculate
propeller
efficiency
Calculate lift
and drag
Aircraft on
ground?
Yes
Calculate ground
friction drag and
reverse thrust if
applicable
No
Determine
Pshaft and
thrust
Scale max gas
turbine power
based on altitude
and speed
No
Determine Pgasturb
based on power
split
No
Pgasturb
more than max
turboprop
power?
Determine
derivatives
No
Constant power
operating mode?
Yes
Determine power
setting
Pgasturb = Pshaft
Calculate SFC
Scale max gas
turbine power
based on altitude
and speed
Determine Pem and
Pbat
Pgasturb
more than max
turboprop
power?
Yes
Pgasturb is max gas
turbine power
No
End
Yes
Speed and
altitude = 0?
Determine power
setting
Yes
Calculate
emissions
Calculate
new state
matrix
Determine change
in battery energy
and weight
Pgasturb is max gas
turbine power
Calculate SFC
Determine
change in
aircraft
weight
Determine change
in fuel weight
Determine change
in battery energy
and mass
Determine Pem and
Pbat
Figure 3.21: Flow chart of the landing phase
46
3. M ETHODOLOGY
3.4.6. H OLD /L OITER
The hold or loiter phase is used when the extended mission is calculated. It takes place when the
aircraft has to hold for a certain amount of time before landing. Figure 3.22 shows how this flight
phase is determined. Since during the entire phase the altitude and speed are constant, some parameters can be calculated outside the iteration loop, improving computation time. Firstly, the drag
polar and secondly the maximum - and idle gas turbine power calculations are moved outside the
iteration loop. Once the iteration is started, the propeller efficiency is determined based on the
thrust at the previous time step and the drag polar is retrimmed based on the burnt fuel and battery
weight increase. Next, the lift and drag are determined in order to have the highest possible L/D.
Since for the loiter phase it would be beneficial to fly using the C L /C D that results in the maximum
endurance (minimum power required), flying at maximum L/D is actually not the best strategy for
3
the loiter phase. It would be better to fly at maximum C L2 /C D , however, this is not implemented in
3
the current version of the Initiator. Making the change from maximum C L /C D to maximum C L2 /C D
will have little effect on the overall result of the mission analysis.
Based on this lift and drag, a target velocity is calculated. If the aircraft is flying faster than this
target velocity, the shaft power is set to idle gas turbine power (and P em = 0). Should the aircraft be
flying slower than this target speed, the power is increased to half the total maximum power. If the
aircraft is flying at the target velocity the shaft power is determined in accordance to Equation 3.33
9
.
When using the power split operating mode, the rest of the iteration is very similar as to what
was used for the cruise phase. For the constant gas turbine power operating mode, there are a few
differences. It was chosen to let the gas turbine provide all of the shaft power for the entire phase
(except when the gas turbine power can not provide the necessary power). This was chosen because
for a normal mission this flight phase would not take place, and as such it would be much more
efficient to bring the necessary reserve fuel instead of providing a lot of extra batteries, due to the
much higher specific energy of fuel. Also, since the power requirement for this phase is generally
smaller compared to the cruise phase, it would not be beneficial in terms of SFC to let the gas turbine
only provide part of the total power requirement.
From this gas turbine power, the power setting is determined from which in turn the SFC is
calculated. Next, the electric motor - and battery power are determined and the change in battery
and fuel mass. Once the required loiter time is achieved, the iteration stops and the final descent
phase is started (from loiter altitude to landing altitude). Since flight path angle, as well as speed
and altitude are constant during this flight phase, no figure of the aircraft state is presented.
9 If the aircraft isn’t flying at the target velocity the lift and drag polars are determined for the correct aircraft velocity, not
the target velocity.
3.4. C LASS 2.5 B ATTERY AND F UEL S IZING
Aircraft state
at end take-off
Determine
max Pgasturb
and Pidle
Determine
drag polar
Relevant
settings
47
Retrim drag
polar
Determine Pgasturb
based on power
split
No
Calculate
propeller
efficiency
Determine
CL,CD for
max L/D
Constant power
operating mode?
Determine Pshaft
based on target
velocity
No
No
Pgasturb
more than max
turboprop
power?
Yes
Determine power
setting
Determine Pgasturb
Calculate SFC
Determine power
setting
Loiter time
reached?
Determine Pem and
Pbat
Calculate SFC
Calculate
new state
matrix
Determine change
in battery energy
and weight
Determine Pem and
Pbat
Calculate
emissions
Determine
derivative of power
split
Determine
change in
aircraft
weight
Determine change
in fuel weight
Yes
Pgasturb is max gas
turbine power
End
Yes
Figure 3.22: Flow chart of the loiter phase
Determine change
in battery energy
and mass
48
3. M ETHODOLOGY
3.5. C OMPARISON BETWEEN C LASS 2 AND C LASS 2.5 SIZING
No validation of the above methods is possible due to the lack of comparable design studies for
hybrid-electric aircraft. For this reason it is interesting to compare the results of the class 2 and
class 2.5 methods to check whether they correspond or not. First it is shown what kind of data is
generated by the class 2.5 method. All results shown in this Section are generated by running the
relevant modules once with a certain set of inputs. They are not the result of a design iteration so
they will not correspond with the results presented in Chapter 4.
3.5.1. M ISSION ANALYSIS RESULTS
Although the class 2 sizing will result in just one number for the fuel and battery sizing of the entire
mission, the mission analysis allows for a more detailed look at the entire mission and each flight
phase to see what happens during each phase. In this section an overview is given of these results
of the mission analysis in order to paint a better picture of the kinds of results that can be expected
from the module as well as to check whether logical and realistic results are achieved 10 . All data
shown here is generated for a hybrid-electric aircraft using a constant power split of 0.5 over the
entire mission, apart from the descent phases where no power split is used. The battery energy
density is 1000 Wh/kg. The requirements are the same as for the ATR72-600 and all other inputs
are as shown in Table 4.3. No data is shown for the constant gas turbine power operating mode. In
section 4.2.3 the comparison between the operating modes is made.
Figure 3.23 shows the state of the aircraft during the entire mission, including deviation and
loiter. Since the required deviation range is only 300 km, the aircraft does not complete the climb
to cruise altitude before descent has to be set in again. For this reason, no secondary cruise phase
is present for this particular mission. Although the take-off and landing phase are present they can
not be seen in Figure 3.23 because they occur for a very small part of the mission. The reason for the
spikes in the graph, especially for γ, is because when the aircraft changes state (for example when
descent sets in) the derivatives become very large momentarily resulting in the peaks visible in the
graph. These peaks only last for 1 time step and as such will not have an effect on the overall result.
Since a constant split of 0.5 is used the power of the gas turbine and electric motor are equal
during the entire mission apart from the descent phase. However, since the required gas turbine
power during the climb phase is more than the maximum gas turbine power the split of 0.5 is only
valid for the beginning of the climb phase, afterwards, the power split decreases slightly since the
electric motor power remains constant, see Figure 3.24.
Figure 3.25 shows the battery and fuel mass that is used during the mission. Any point along
the graph shows the battery and fuel mass used up until that point in the mission. The same graph
could be made for battery and fuel energy, which would show exactly the same trends. As one would
expect, during the climb phases the battery and fuel mass increase the fastest, although the largest
contribution is still from the cruise phase.
10 Ggain, since no real validation is possible.
3.5. C OMPARISON BETWEEN C LASS 2 AND C LASS 2.5 SIZING
49
Descent 3
Cruise
Loiter
1
Descent 2
1.5
Descent 1
Climb 1
altitude (m)
2
Climb 2
·104
0.5
0
0
200
400
600
800
1,000
1,200
1,400
1,600
1,800
2,000
0
200
400
600
800
1,000
1,200
1,400
1,600
1,800
2,000
0
200
400
600
800
1,000
1,200
1,400
1,600
1,800
2,000
speed (m/s)
150
100
50
0
γ (deg)
10
0
−10
−20
range (km)
Figure 3.23: State of an arbitrary hybrid-electric aircraft during the entire mission, including deviation and loiter
50
3. M ETHODOLOGY
Shaft Power
Electric Motor Power
Gas Turbine Power
Descent 3
Loiter
Cruise
Descent 2
4.5
Descent 1
Climb 1
5
Climb 2
·106
4
Power [W]
3.5
3
2.5
2
1.5
1
0.5
0
0
200
400
600
800
1,000
1,200
1,400
1,600
1,800
2,000
Range [km]
Figure 3.24: Shaft -, gas turbine - and electric motor power during the entire mission for a constant power split of 0.5
Mass [kg]
Descent 3
Loiter
Cruise
Descent 2
4,000
Climb 2
Climb 1
5,000
Fuel
Descent 1
Battery
3,000
2,000
1,000
0
0
200
400
600
800
1,000
1,200
1,400
1,600
range [km]
Figure 3.25: Battery- and fuel weight used during the entire mission, for a constant power split of 0.5
1,800
2,000
3.5. C OMPARISON BETWEEN C LASS 2 AND C LASS 2.5 SIZING
51
3.5.2. C OMPARISON
In this section, the comparison is made in terms of fuel and battery mass for the entire mission for
a range of different inputs. It is very important to note that the results shown here are generated
by running both sizing methods only once with the same inputs, not for an entire design loop. The
results will therefore not necessarily correspond with the result shown in the next chapter. All the
results are generated with the requirements shown in Table 4.1 and the inputs shown in Table 4.3
and for a battery energy density of 1500 Wh/kg.
First the results for the power split operating mode are compared, and are shown in Table 3.2.
For all results a constant power split over the entire mission is used. Four different power splits are
examined: 1 (purely electric), 0.66, 0.33 and 0 (only gas turbine).
Table 3.2: Comparison between the class 2 and class 2.5 sizing methods for constant power splits ranging from 0.00 to
1.00
Class 2 method
Class 2.5 method
Difference
S = 1.00
mfuel [kg]
mbat [kg]
0
5317
0
5635
0.0 %
+ 6.0 %
S = 0.66
mfuel [kg]
mbat [kg]
709
3602
661
3428
– 6.8 %
– 4.8 %
S = 0.33
mfuel [kg]
mbat [kg]
1209
1835
1248
1645
+ 3.2 %
– 10.3 %
S = 0.00
mfuel [kg]
mbat [kg]
1735
0
1804
0
+ 4.0 %
0.0 %
As can be seen, both methods correspond adequately in terms of the battery and fuel weight
found. The difference is at most around 10 % for the battery weight at a constant power split of
0.66. When using a variable power split over the entire mission the differences might become larger
since especially the class 2 methods for certain flight phases are only rough estimations. However,
any inaccuracies in the class 2 methods will not have an influence on the final design since those
outputs are only used to have a first estimation and are overruled later on in the design loop by the
output of the class 2.5 sizing method. More accurate results for the battery mass might be found
when using the hybrid-electric range equation to determine the battery mass, as well as the fuel
mass for the cruise phase.
Since there are distinct differences in the methods used for determining the battery - and fuel
mass for the two different operating modes, the same comparison as before also has to be made for
the constant gas turbine power operating mode. Table 3.3 shows the results of this comparison for
multiple input gas turbine powers. The gas turbine powers that are compared vary from 0.1 MW to
3 MW. The reason a gas turbine power of 0 is not used (which should give about the same result as
for S = 1.00) is that the Initiator program does not converge for a very low gas turbine power (less
than 10 kW), for the chosen input parameters.
From table 3.3 it is clear that there are more significant differences between the class 2 and class
2.5 sizing methods for this operating mode compared to the constant power split operating mode.
Especially the fuel weight is consistently overestimated in the Class 2 sizing method. This is because
the decrease in SFC that results from using this operating mode can not be accurately determined in
the class 2 method, as well as general inaccuracies that result from using a less complex and simpler
method.
The class 2 battery weight estimation on the other hand shows slight better correspondence to
the class 2.5 method, apart from large differences when the maximum gas turbine power becomes
52
3. M ETHODOLOGY
large (≈ 3 MW). When the gas turbine power is that large, the batteries can be charged during the
cruise phase using the excess power. This mechanism can not be implemented in the class 2 method
11
and as such the battery weight required will be overestimated in the class 2 method.
Table 3.3: Comparison between the class 2 and class 2.5 sizing methods for input gas turbine powers ranging from 0.1
MW to 3 MW
Pgasturbmax [MW]
Class 2 method
Class 2.5 method
Difference
0.1
mfuel [kg]
mbat [kg]
127
4518
72
5146
– 43.3 %
+ 13.9 %
1
mfuel [kg]
mbat [kg]
882
2391
713
2930
– 19.2 %
+ 22.5 %
2
mfuel [kg]
mbat [kg]
1720
986
1289
1248
– 25.0 %
+ 10.3 %
3
mfuel [kg]
mbat [kg]
2559
682
1870
129
– 27.0 %
– 81.1 %
Although the class 2 method for the constant gas turbine power operating mode is not as accurate as the method for the power split operating mode this will not have an adverse effect on the
ultimate design(s). As mentioned before, the class 2 method is only used to have a first guess in the
beginning of the design loop and is later on overwritten with more accurate results from the class 2.5
sizing process. This means that, for the constant gas turbine power operating mode, the program
will take slightly longer to converge to a design since the first "guess" is not as accurate.
3.6. E LECTRIC M OTOR S IZING
The electric motor consists of not only the motor itself, but also the cryocooler which is required
to have superconducting properties. The size and weight of the electric motor is dependent on the
maximum power it has to deliver. This power is either found from the take-off power loading (taking
into account the power split or the gas turbine power) or from the mission analysis, depending on
the location in the design iteration. A certain electric motor power density is chosen, by default a
value of 15 kW/kg is used. This is a conservative estimate based upon predictions by NASA, IEEE
and others [47] [30] [28]. However, as mentioned before, the contribution of the crycooler also has
to be taken into account. This cryocooler not only adds weight but also requires power to function.
This power is dependent on the maximum rated power of the electric motor. NASA states that such
a cryocooler is expected to have a power requirement of 0.16% of the maximum rated power of the
electric motor [28]. However, this seems a very optimistic number when compared to today’s state
of the art cryocoolers. For this reason a default value of 0.45% of the maximum electric motor power
is chosen. With the power of the cryocooler known the weight is determined by the chosen input
power density. By default 3 kg/kW [28] is used for the cryocooler power density (without the electric
motor). The volume of the engine is determined by the volumetric power density. Figure 3.26 shows
the variation of the electric motor weight, including the crycooler, with the maximum rated electric
motor power.
11 Because a mission analysis is required to keep track of the SOC of the batteries during the entire mission.
53
Electric motor + cryocooler weight [kg]
3.7. W IRING
250
200
150
100
50
0
0
0.5
1
1.5
2
2.5
Maximum electric motor power [W]
3
·106
Figure 3.26: Variation of the electric motor and cryocooler weight with respect to the maximum electric motor power
3.7. W IRING
The wiring encompasses everything that is needed to make the connection between the battery
pack(s) and the electric motor. Since high temperature superconducting motors, used for aerospace
applications, require AC power [30] and batteries deliver DC power, an inverter has to be present as
well. This inverter not only changes the current from DC to AC but is also able to transform the
voltage from the battery output voltage to the electric motor input voltage. Since it was chosen
not to use high temperature supercooling for the wiring, the wiring weight can be estimated more
accurately, based on real cable data. For a given voltage and cable length the wiring weight will only
depend on the current running through the cable. This current in turn will depend on the power
(for again a fixed voltage). To keep the cable diameter (and thus also the weight) as low as possible
the voltage has to be quite high. This voltage has to be chosen first, for all designs considered in
this project a voltage of 6000 V AC is chosen. Based on the power that has to run through the cable,
P
a certain current is obtained (I = U
). It was chosen to use aluminium wiring over copper wiring
since aluminium wiring has a lower weight for the same voltage and current 12 . Using cable data
obtained from Synergy Cables Ltd. [48] a graph can be constructed which plots the current vs the
cable weight per unit length for a cable carrying 6 kV, see Figure 3.27. This cable data also includes
the weight of the insulation.
12 Although it has a larger diameter due to aluminium having more resistance than copper
54
3. M ETHODOLOGY
8
Cable weight [kg/m]
7
6
5
4
3
17.703∗A−622.45
1000
2
1
100
150
200
250
300
350
400
450
Cable current [A]
Figure 3.27: Cable weight as a function of current for a cable rated at 6 kV
In the above figure the red line represents the trend line constructed from the data. This trendline is used in the Initiator program. Should the calculated current lie outside the range shown in
Figure 3.27 a different cable voltage should be chosen. At this time however, only one cable voltage
is implemented, namely 6 kV.
Using the length of the cable, the total mass of a cable can be known. This length is determined
by the location of the battery pack and the electric motor. The shortest distance between these two
components is taken and multiplied with a factor of 1.5 in order to account for the path the cable
has to take 13 . The found mass also has to be multiplied with the number of cables. For redundancy
by default 2 cables are chosen.
As mentioned previously, an inverter also has to be present. Using todays technology, this inverter would be too heavy and large. For this reason it is chosen to also use HTS technology for this
component. The weight is dependent on the maximum power it has to handle. Based on literature
a constant power density of 20 kW/kg is chosen [47]. This number includes the cryocooler as well.
The efficiency of the inverter, including the cryocooler, are estimated to be as high as 99.5% [47] [49].
The efficiency at take-off would be about 0.25% lower [49]. But since the take-off phase is short, this
difference is neglected.
3.8. OTHER C OMPONENTS
In this section a brief discussion is given of some other small changes to the Initiator, namely the
battery cooling, the implementation of the configuration and the fuselage weight estimation.
Batteries can produce a lot of heat. The amount of heat produced is dependent on the power
the batteries deliver and the efficiency. As such, a battery cooling system should be incorporated
in the hybrid-electric aircraft design. Finding the best method to cool the batteries and designing
a cooling system is a topic for a more detailed design study. Possibilities include using air cooling,
using the cryocooler that is needed for the inverter and electric motor, etc.. Although designing this
cooling system is not performed in this design study, the added weight of such a cooling system has
to be taken into account. As such a simple method for estimating the battery cooling weight has to
be found.
13 The wiring will not follow the shortest route from the battery to the electric engine since the cable would have to pass
through the cabin floor and obstruct many other components such as landing gear stowage, see Section 3.9.
3.9. C OMPONENT P LACEMENT
55
The maximum heat the batteries produce is given by:
Q̇ bat = P bat ∗ (1 − η bat )
(3.34)
A method for determining the air conditioning weight is already present in the Initiator. This is
based on the number of people that are present in the cabin. The average human produces about
120 Watt based on the average calorific intake of 2800 Kcal per day. Using this fact the heat that the
batteries emit can be equated to a certain amount of "extra" passengers that are taken on board.
And as such, using the same method for the calculation of the air conditioning weight the battery
cooling weight can be estimated. This is a very rough estimation that might not be very accurate,
and can only be used to have a ballpark figure.
Some major changes also had to be made in order to change the configuration to something
that represents the configuration shown in Figure 2.1. Changes include changing the wing location,
the fuselage shape and the gas turbine and propeller location.
The fuselage weight estimation includes a calculation of the longitudinal loads on the fuselage
based on all the relevant components and their placement. Obviously this has to be adapted in
order to include the contribution of the battery, inverter, wiring and the electric motor.
3.9. C OMPONENT P LACEMENT
The placement of all the components such as battery, inverter, wiring, electric motor, etc.. have
a large influence on the final design. For example it is beneficial to place the battery as close as
possible to the electric motor in order for the length of the wiring to be as short as possible. The
electric motor on the other hand has to be placed at the rear of the fuselage, close to the gas turbine
for the mechanical coupling to not be too heavy. As a result the "optimal" placement of all the
electrical components would be as far to the rear of the fuselage as possible. However, this is not
possible for two reasons. Firstly, the lack of space at the rear of the fuselage for all the components
and more critically, the position of the center of gravity of the aircraft would move too far to the rear,
making the aircraft unstable.
For these reasons the battery, which is often the heaviest component (depends on the factor
of hybridization), is placed further to the front, near the leading edge of the root of the wing (in
terms of x-location). Of course the batteries can not be placed inside the cabin, so they are placed
underneath the floor of the cabin (no cargo is present there). The height of the battery pack is
thus limited by the space underneath the cabin floor, while the width is limited by the edges of
the fuselage. So the only variable (as a function of the battery volume) is the length of the battery
pack. Should the battery pack interfere with the space required for stowing the landing gear, the
battery pack is moved forward such that there is still enough room for the landing gear. This has the
undesirable consequence that for very high hybridization factors (heavy battery pack) the battery
has to be placed quite far to the front, moving the total center of gravity of the aircraft also further to
the front than desired, even sometimes exceeding the load limit of the front landing gear. A possible
solution to this problem is too split the battery pack in two, placing one part in front of the landing
gear and one part to the rear of landing gear. However, this is not implemented in the current version
of the program because, on one hand, it is impossible to automatically assess when this would be
beneficial to do, but also, if the center of gravity is too far to the front for this to occur, the battery
pack has to have such a large volume (and weight) that such a design is not a feasible design anyway
(apart from the case where the battery gravimetric energy density is large and the volumetric energy
density is low). Figures 4.27 to 4.30 illustrate the component placement for a hybrid-electric aircraft.
56
3. M ETHODOLOGY
3.10. I MPLEMENTATION
How everything mentioned in this chapter is implemented in the Initiator is discussed in this section. First and foremost, some new parts are constructed: the electric motor, the batteries and the
wiring + inverter. The battery cooling is added as part of the aircraft "systems", as such no new part
is constructed for this. Each of these parts handles the properties of their respective part, such as
mass and center of gravity location but also maximum power for the electric motor or volume for
the batteries. These properties can then be read by different modules when needed. Both the battery part and the electric motor part also have geometrical properties in order to be able to plot their
size and location. This is not the case for the wiring.
For the class 2 weight estimation module some new sub-modules have been added to determine
the weight of the extra parts and some other sub-modules have been modified to be able to cope
with turboprop aircraft (such as the engine weight module). A separate instance of the mission
analysis module is created which is used when either a turboprop or a hybrid-electric aircraft is
used as input. The original mission analysis module has been left (almost) unmodified and is used
for turbofan aircraft.
The input file with requirements remains largely unmodified whether the aircraft is hybridelectric or not. However, many new inputs have been added to the settings file which are listed
in Table 3.4.
3.11. L IMITATIONS
Implementing the above methods results in some limitations which are discussed here. First and
foremost, since the design of a passenger transport aircraft with more than 19 seats and a MTOM
of more than 8619 kg14 is considered, one would expect to use far-25 requirements [37]. These far25 requirements are used for designing the reference aircraft, however, they can not be used for
designing the hybrid-electric aircraft. This is due to several requirements, pertaining to the oneengine inoperative requirements, which are impossible to take into account in the beginning of
the design of the hybrid-electric aircraft. If you consider one engine to be the electric motor and
another engine to be the gas turbine it might be possible in some configurations to meet these
requirements. However, a clutch would have to be present between these two engines and both
engines would have to have about the same maximum power, which is not the case in the majority of
the designs under consideration. As of yet, no certification process exists for hybrid-electric aircraft,
and, since it is most likely impossible to meet the far-25 requirements in their current form, the far23 requirements [50] are used for all the hybrid-electric designs considered here.
As discussed previously, no power off-take from the batteries is considered. All the power goes
to the electric motor. It might be possible to use the battery power to replace all the hydraulic, mechanical, etc.. subsystems with electric system to increase reliability, maintainability and possibly
even decrease weight. This is the so called more-electric-aircraft concept. However, this is not considered in this design study as this would be outside the scope of the project as well as no reliable
methods exist for sizing such an aircraft.
At the start of the design loop (but not part of the design iteration, see Figure 3.1) a class 1 weight
estimation is performed. Since this weight estimation is entirely based upon a database of existing
reference aircraft, it does not take into account whether the to design aircraft is a hybrid-electric
aircraft or not. As such, the first class 1 estimation is very inaccurate for hybrid-electric aircraft.
Afterwards a class 2 and 2.5 weight estimation is performed which overwrite the class 1 estimation,
which means a bad class 1 estimation will not have an effect on the ultimate design. The design
iteration might take a little longer because of the bad first guess. The current implementation of the
class 2 weight estimation for the batteries and fuel produces inaccurate results in some cases (see
Section 3.5.2). The accuracy can be improved by implementing the hybrid-electric range equation
14 19000 pounds
3.11. L IMITATIONS
57
to find both the battery and fuel weight, and not just the fuel weight. This adaptation will not have
an effect on the ultimate design since later in the design iteration the mission analysis is performed
(class 2.5 sizing).
There are also a few limitations pertaining to what range of inputs can be selected. An error
occurs when choosing a power split that would result in a fully electric cruise or hold phase (S =
1) due to the hybrid-electric range equation (Equation 3.20) not finding a solution. A workaround
is selecting a power split of 0.9999. The difference in the final design is negligible. Also, when the
found battery mass is very small (< 50 kg) the longitudinal load on the fuselage is ignored. This
results in a warning during the fuselage weight estimation, however, this has further no effect on
the design. This does not occur when designing a non-hybrid aircraft since the battery part is never
created.
When designing a hybrid-electric aircraft using the constant gas turbine power operating mode,
the calculation of the range at the end of the design iteration is not correct since this uses the hybridelectric range equation (Equation 3.20) to estimate the range and this equation is only valid for the
power split operating mode (since the power split is included in the equation).
The design loop itself also takes longer for a hybrid-electric aircraft compared to a non-hybrid
aircraft. This is mostly due to the extra variables that have to be calculated in the mission analysis.
Although it differs from design to design, in general, the design convergence takes about 5 minutes
longer when using the power split operating mode and 10 minutes (even up to 15 minutes in extreme cases) longer when using the constant gas turbine power operating mode. The reason for the
difference between the two operating modes is the less accurate class 2 weight estimation for the
constant gas turbine operating mode (as was discussed in Section 3.5.2). Since the first guess (class
2 estimation) isn’t always accurate, the class 2.5 weight estimation requires more iterations before
converging. For small input gas turbine powers approaching the infeasibility domain the entire design loop can take significantly longer, in some extreme cases even more than 1 hour. The mission
analysis itself also takes slightly longer: 2-3 seconds longer per mission analysis. This is due to the
difference in implementation and the extra computing power required for, for example, searching
for the optimal power setting during the cruise phase. The above mentioned computing times are
only a ballpark figure and depend on the computing power available. Although a lot of optimization
of the code is already performed, the computation time can be further improved by optimizing the
code more.
58
3. M ETHODOLOGY
Table 3.4: New input parameters that are needed in the Initiator program when designing a hybrid-electric aircraft
Parameter
Hybrid
e bat
vol bat
∆m bat
Reserve battery
η em
η el ec
η bat
η pr op
p em
vE M
em size ratio
P cr yo
p cr yo
p i nv
Uc abl e
Nc abl es
Mode
S t akeo f f
S cl i mb
S pr ecr ui se
S end cr ui se
S l and i ng
S hol d
P g ast ur b
Description
Lets the program know whether or not a hybridelectric aircraft is being designed, it influences the
shape of the fuselage, location of the gas turbine,
what parts are created and the mission analysis
Specific energy of the battery pack
Volumetric energy density of the battery pack. By
default the same value as the specific energy
The increase in battery mass when battery energy
is used. This is non-zero for lithium-air batteries
Factor of the total battery pack weight that is left as
reserve in order for the battery pack to not fully deplete at the end of the mission which could result
in permanent damage to the batteries
Electric motor efficiency
Efficiency of the wiring-inverter combination
Discharging and charging efficiency of the battery
pack
Propeller efficiency. Used during the class 2 sizing
process. For the mission analysis this is calculated
using the ideal efficiency (Equation 3.5)
Electric motor power to weight ratio
Electric motor power to volume ratio
Electric motor length/diameter. Used for constructing the electric motor with the correct dimensions
Percentage of the maximum electric motor power
required to run the cryocooler of the electric motor
Cryocooler power to weight ratio
Inverter power to volume
Voltage running through the cables connecting the
battery/inverter to the electric motor
Number of cables connecting the battery/inverter
to the electric motor, including those needed for
redundancy
Determines what operating mode is used. 0 =
power split operating mode and 1 = constant gas
turbine operating mode
Power split during the take-off phase
Power split during the climb phase
Power split at the start of the cruise phase
Power split at the end of the cruise phase
Power split during the landing phase
Power split during the hold/loiter phase
Maximum continuous gas turbine power used
when the constant gas turbine operating mode is
selected
Unit
-
Wh/kg
Wh/l
kg/Wh
-
-
kW/kg
kW/l
-
%
kW/kg
kW/kg
V
-
-
W
4
R ESULTS
In this chapter the results are presented. Firstly, the changes made to the Initiator in order to construct the reference aircraft are validated by comparing the reference aircraft to the ATR 72-600.
Next, the results of the hybrid-electric aircraft are given, starting with the effect of a change in the
degree of hybridization or supplied power ratio. Subsequently, a comparison is made between the
two operating modes and an assessment is made whether there is an optimal power split that can
be used. A sensitivity analysis with respect to battery specific energy and aircraft range is also performed. And lastly, one feasible design is investigated in more detail.
4.1. R EFERENCE A IRCRAFT
In this section the comparison is made between the reference aircraft that was designed using the
changes mentioned in Section 3.2 and the ATR 72-600. Table 4.1 shows the requirements of this
aircraft, which are also used as input for the reference aircraft design. The time to climb consists of
two data points, the time it takes (in minutes) to reach a specific altitude (in meter).
Parameter
Payload mass
Number of passengers
Range
Cruise Mach
Cruise altitude
Take-off distance
Landing distance
Time to climb
Value
7500
68
Unit
kg
-
1528
0.45
7500
1333
1067
[17.5, 5400]
km
m
m
m
[min, m]
Table 4.1: Requirements of the ATR 72-600 which are also used as input for the reference aircraft design
Figures 4.1, 4.2 and 4.3 show the difference between the reference aircraft and the ATR in terms
of geometry. The grey aircraft represents the aircraft designed by the initiator while the black lines
show the geometry of the ATR 72-600. As can be seen, both aircraft are very similar in terms of
geometry, showing only slight differences for the fuselage, tail and wing. The landing gear however
appears to be quite a bit longer for the reference aircraft which suggest the landing gear design
module might not give the most accurate results for this type of aircraft, but this does not have a
large effect on the overall design. It might be possible to design a reference aircraft which is an even
59
60
4. R ESULTS
closer match to the ATR by tweaking some settings (such as wing kink location, fuselage shape, etc...
). However this would provide little added value.
Figure 4.1: Front view of the ATR72-600 compared to the reference aircraft
Figure 4.2: Side view of the ATR72-600 compared to the reference aircraft
4.1. R EFERENCE A IRCRAFT
61
Figure 4.3: Top view of the ATR72-600 compared to the reference aircraft
Table 4.2 shows the main parameters of the reference aircraft compared to the ATR 72-600. As
can be seen, the results for the reference aircraft are a very close match to those of the ATR 72600. The largest difference is in the wing area with a difference of only 4.2 %. From this it can
be concluded that the changes made to the Initiator in order for it to be able to design a regional
turboprop aircraft are valid and provide results with sufficient accuracy for a preliminary design. It
is worth noting however, that, although the MTOM of both aircraft are very similar, the mass of the
individual components can differ a lot between the two aircraft. This is partially due to difference
in what is and what isn’t incorporated into each part 1 .
1 For example the definition of what is included in "electrical systems" can differ between the ATR 72-600 and the refer-
ence aircraft.
62
4. R ESULTS
Table 4.2: Parameters comparing the ATR 72-600 to the reference aircraft
Parameter
Max take-off mass
[kg]
Mission fuel mass [kg]
Empty mass [kg]
Propeller
diameter
[m]
Wing Span [m]
Wing Area [m 2 ]
Fuselage Length [m]
ATR 72 -600
22800
Reference aircraft
22340
Difference
- 2.0 %
2000
13010
3.93
2050
12780
3.92
+ 2.4 %
- 1.8 %
- 0.3 %
27.05
61
27.17
26.5
58.54
27
- 2.1 %
- 4.2 %
- 0.6 %
4.2. H YBRID A IRCRAFT
In this section the results for the hybrid-electric aircraft are given. First, the values of various inputs
that are needed for creating the following designs are given. Next, the design space is explored
in terms of the supplied power ratio. After which the difference between the operating modes is
examined and an attempt is made to find the optimum power split.
4.2.1. I NPUTS
Before the results of the hybrid aircraft are presented, the used input values are discussed. This is
necessary because these input settings have a large influence on the final design. Table 4.3 shows
the inputs with their respectively chosen values. Certain inputs such as battery specific energy,
power split or gas turbine power (depending on chosen operating mode) are not fixed but will vary
throughout this chapter as these values have a very large influence on the results and their value can
not be known for sure.
Table 4.3: Input values that are used for each design considered in this chapter
Parameter
Hybrid
∆Wbat
Reserve battery
η em
η el ec
η bat
η pr op
pE M
em size ratio
P cr yo
p cr yo
p i nv
Uc abl e
Nc abl e
Value
1
0.000192
0.1
0.98
0.97
0.98
0.85
15
2
0.45
0.33
25
6000
2
Unit
[-]
kg/Wh
[-]
[-]
[-]
[-]
[-]
[kW/kg]
[-]
[%]
[kW/kg]
[kW/kg]
[V]
[-]
The description of the parameters in Table 4.3 can be found in Table 3.4. In the previous chapter
4.2. H YBRID A IRCRAFT
63
some more explanation is given as to why a certain value is used for certain parameters 2 .
4.2.2. S UPPLIED P OWER R ATIO
The effect that making the aircraft more hybrid is investigated here. For this purpose the influence
of the supplied power ratio is examined. One can also choose to examine the effect of the degree
of hybridization, the results will be very similar. The reason for choosing the supplied power ratio
over the degree of hybridization is that it gives a better idea of how much total power and energy is
delivered to the propeller from both the electric motor and the gas turbine, thus allowing for a better understanding of how "hybrid" a certain design is. Also, since the energy of the fuel is generally
much larger than the energy contained in the batteries 3 the values for the degree of hybridization
tend to be much lower compared to the supplied power ratio. Consequently the values for the degree of hybridization tend to be more clustered and do not give a very intuitive representation of
how much electric motor - and gas turbine energy is actually used during the mission.
In this section all hybrid designs under investigation have been constructed using the "power
split" operating mode, however all effects can also be observed for the "constant gas turbine power"
operating mode. In section 4.2.3 the difference between these two operating modes is examined.
The power split chosen for each design in this section is constant throughout the mission (S i =
S i +1 = const ant ). In Section 4.2.4 it is examined whether there is a better alternative to using a
constant power split. When using a constant power split, the chosen power split is approximately
equal to the supplied power ratio (S const ant ≈ Φ). Slight difference in both values might occur due
to the power split not being constant for the entire climb phase: P em > S 2 ∗ P sha f t for most of the
climb phase.
As mentioned before, all parameters shown in Table 4.3 are fixed. The only variables are the
power splits for each mission phase and the battery specific energy. As discussed in Section 2.2.1
the prognosis for battery specific energy in the year 2035 lies between 750 Wh/kg and 1500 Wh/kg.
As a result, in this section, these two battery energy densities are chosen, as well as 1000 Wh/kg. All
designs with battery energy densities between 750 and 1500 Wh/kg will lie between the boundaries
set by the aforementioned specific energies.
First, the battery and fuel mass are examined. As one would expect, the battery mass increases
with increasing supplied power ratio, see Figure 4.4. The slope of the battery mass highly depends
on the battery specific energy. While the slope is almost linear when e bat = 1500 Wh/kg, it is almost
exponential when e bat = 750 Wh/kg. This is due to the snowball effect caused by the increase in
MTOM, see Figure 4.6. With an increase in battery mass comes an increase in MTOM which in turn
increases the total energy requirement, which again increases the battery mass and so on. For this
reason there is an upper limit to the achievable supplied power ratio 4 . After a certain point, the
increase in available energy of taking more batteries on board is less than the increase in required
energy that comes from taking these batteries on board. As such, after this point, the MTOM will
keep increasing in every iteration, and not converge to a solution.
The decrease in fuel mass with supplied power ratio (Figure 4.5) appears to be more linear, although with a different gradient for a different battery specific energy. It is worth noting that the
benefits in terms of total fuel mass of having a higher battery specific energy for a low supplied
power ratio (Φ < 0.15) are almost non-existent due to the relatively small increase in MTOM. Both
for the decrease in fuel mass and the increase in battery mass the benefits of having a higher battery
specific energy increase greatly when getting to higher supplied power ratios. In Section 4.3.2 the
influence of the battery specific energy is investigated in more detail.
In Figure 4.5 and 4.6 the reference aircraft fuel mass and maximum take-off mass are also shown.
2 See Section 3.6 for most values
3 Due to the much higher specific energy of fuel compared to the battery pack.
4 For a battery energy density less than 1500 Wh/kg
64
4. R ESULTS
The reason the values for the reference aircraft do not correspond to the values for Φ = 0 is due to
the influence of the configuration itself. Although the requirements are the same, the fact that there
is only one engine (and no engine drag), as well as the different wing and center of gravity location
result in a slightly lighter aircraft which uses less fuel. The influence of boundary layer ingestion and
contra-rotating propellers are not taken into account.
In Figure 4.7, the influence of the supplied power ratio on the maximum electric motor power is
shown. This is an important metric since not only the electric motor mass depends on this factor,
but also the wiring mass, inverter mass and the battery cooling mass. Especially for the electric motor power the influence of the battery specific energy at low supplied power ratios is negligible. This
is again due to the only slight increase in MTOM and the resulting small increase in take-off and
climb power required. Nevertheless, Figure 4.8 shows the variation of the mass of all components
which depend on P em with supplied power ratio for a battery energy density of 1500 Wh/kg. The
same trends can be observed for all other battery energy densities. The contribution of the battery
cooling appears to decrease with an increase in supplied power ratio. However, as mentioned before, the battery cooling is very hard to size in the preliminary design phase and thus the values are
only a rough estimation.
And finally, in Figure 4.9 the variation of the gas turbine mass with supplied power ratio is shown.
Since the gas turbine mass depends on the maximum power the gas turbine has to deliver, it stands
to reason that the gas turbine mass variation is approximately inversely proportional to the electric
motor power variation (Figure 4.7).
It is important to note that not all designs in this section are feasible since some designs have
stability issues due to the location of the center of gravity. A low supplied power ratio results (in
general) in an aircraft with a light battery and a heavy gas turbine. Since the configuration is fixed,
this might result in a center of gravity which is too far to the rear. This could be solved by placing
the batteries further to the front of the aircraft or moving the wing further to the rear, etc.. On the
other hand, when the supplied power ratio becomes large, the center of gravity can move too far
to the front due to the heavy battery. Where exactly this boundary of feasibility lies is very hard
to predict, because it depends heavily on the location of the various components, which can be
changed relatively easily. The battery specific energy also has a large influence on this range. In
general a supplied power ratio between 0.3 and 0.6 appears to be feasible.
·104
e bat = 1500 Wh/kg
e bat = 1000 Wh/kg
e bat = 750 Wh/kg
Battery Mass [kg]
1
0.5
↓ Reference aircraft fuel weight
0
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Supplied Power Ratio [-]
Figure 4.4: Battery mass vs supplied power ratio for multiple battery energy densities
0.8
0.9
1
4.2. H YBRID A IRCRAFT
65
2,500
↓ Reference aircraft fuel weight
Fuel Mass [kg]
2,000
1,500
1,000
e bat = 1500 Wh/kg
e bat = 1000 Wh/kg
e bat = 750 Wh/kg
500
0
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0.9
1
Supplied Power Ratio [-]
Figure 4.5: Fuel mass vs supplied power ratio for multiple battery energy densities
4
·104
e bat = 1500 Wh/kg
e bat = 1000 Wh/kg
e bat = 750 Wh/kg
MTOM [kg]
3
↑ Reference aircraft MTOW
2
1
0
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Supplied Power Ratio [-]
Figure 4.6: Maximum take-off mass vs supplied power ratio for multiple battery energy densities
66
4. R ESULTS
Maximum P em
6
·106
e bat = 1500 Wh/kg
e bat = 1000 Wh/kg
e bat = 750 Wh/kg
4
2
0
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Supplied Power Ratio [-]
Figure 4.7: Maximum electric motor power vs supplied power ratio for multiple battery energy densities
1,400
Total
Electric Motor
Wiring and Inverter
Battery Cooling
1,200
Mass [kg]
1,000
800
600
400
200
0
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Supplied Power Ratio [-]
Figure 4.8: The mass of the components making up the electrical part of the powertrain (minus the batteries) vs supplied
power ratio for a battery energy density of 1500 Wh/kg
4.2. H YBRID A IRCRAFT
67
Gas Turbine Mass [kg]
1,000
e bat = 1500 Wh/kg
e bat = 1000 Wh/kg
e bat = 750 Wh/kg
800
600
400
200
0
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Supplied Power Ratio [-]
Figure 4.9: mass of the gas turbine vs supplied power ratio for multiple battery energy densities
0.9
1
68
4. R ESULTS
4.2.3. O PERATING M ODES
Maximum Continuous Gas Turbine Power [W]
In this section it is examined whether there is a difference in designs using the power split operating mode compared to the constant gas turbine power operating mode using otherwise the same
inputs. To be able to compare these operating modes, a certain measure for how hybrid a certain
design is has to be introduced. For this purpose the supplied power ratio is used again. Figure 4.10
shows the relation between the input gas turbine power and the supplied power ratio. This relation is approximately linear with a slope that depends on the chosen battery specific energy. The
difference is due to the lighter aircraft resulting from a larger battery specific energy. A lighter aircraft will have a lower supplied power ratio for the same gas turbine power, since less total energy
is required but the gas turbine energy stays the same. Again, for all designs using the power split
operating mode considered in this section, a constant power split was used over the entire mission
(S i = S i +1 = const ant ). This might not be the most optimal control strategy but more info on that
topic can be found in Section 4.2.4.
3
·106
e bat = 1500 Wh/kg
e bat = 1000 Wh/kg
e bat = 750 Wh/kg
2.5
2
1.5
1
0.5
0
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Supplied Power Ratio [-]
Figure 4.10: The maximum continuous gas turbine power vs the supplied power ratio for battery energy densities of 750,
1000 and 1500 Wh/kg
The reasoning behind the constant power operating mode is the decrease in SFC, especially
for the cruise phase. Figure 4.11 and 4.12 show the variation in P em , P g ast ur b and P sha f t for two
designs. The first one is constructed using the power split operating mode and the second one
using the constant gas turbine operating mode. Both use exactly the same inputs (Table 4.3 and
e bat = 1000 Wh/kg) and have a resulting supplied power ratio of approximately 0.25. It can clearly
be seen that the constant gas turbine operating mode results in a design with less variation in the
delivered gas turbine power, resulting in a lower SFC. 5 . It does have the downside that the electric
motor needs to compensate more for the peaks in the required shaft power. The average SFC during
the cruise phase is 291 g/kWh for the constant gas turbine power operating mode, compared to 300
g/kWh for the power split operating mode. This might not seem like a large difference, however,
over the entire cruise phase, it does result in a non-negligible difference in fuel mass.
5 Since a larger power setting is used for the cruise phase
4.2. H YBRID A IRCRAFT
69
Descent 3
Loiter
Cruise
Descent 2
Gas Turbine Power
Climb 2
Climb 1
5
Electric Motor Power
Descent 1
Shaft Power
·106
Power [W]
4
3
2
1
0
0
200
400
600
800
1,000
1,200
1,400
1,600
1,800
2,000
Range [km]
Figure 4.11: Shaft -, electric motor - and gas turbine power during the entire mission for a constant power split, resulting
in a supplied power ratio of 0.25 using a battery specific energy of 1000 Wh/kg.
Descent 3
Loiter
Cruise
Descent 2
Gas Turbine Power
Climb 2
Climb 1
5
Electric Motor Power
Descent 1
Shaft Power
·106
Power [W]
4
3
2
1
0
0
200
400
600
800
1,000
1,200
1,400
1,600
1,800
2,000
Range [km]
Figure 4.12: Shaft -, electric motor - and gas turbine power during the entire mission for a certain input gas turbine power,
resulting in a supplied power ratio of 0.25 using a battery specific energy of 1000 Wh/kg.
70
4. R ESULTS
When comparing the final designs of both operating modes in terms of fuel - and battery mass
(Figure 4.13 and 4.14) it can be seen that for the same supplied power ratio the constant power operating mode results in a design with a slightly lower fuel mass and the same battery mass. This can
be observed regardless of battery specific energy. For a low supplied power ratio (approximately Φ <
0.15), the fuel mass of the constant gas turbine power operating seems to become larger compared
to the power split operating mode. This is because, for a low supplied power ratio, the gas turbine
power becomes so large that P g ast ur b > P sha f t for the cruise phase. As such the excess gas turbine
power is used for charging the batteries, which has as result that the (partially) charged batteries can
be used for the subsequent flight phases and as such less battery mass needs to be taken on board.
The variation in gas turbine power is less for the constant gas turbine power operating mode.
This has as consequence that the electric motor needs to compensate more for the peaks in required
shaft power (such as during take-off and climb). Figure 4.15 shows that the electric motor power
is significantly larger for the constant gas turbine power operating mode, regardless of supplied
power ratio (except for when Φ = 1 due to no gas turbine being present). Since the electric motor
mass, wiring mass and battery cooling mass are all dependent on this factor, their mass will also be
significantly more for the constant gas turbine power operating mode. However, for the same reason
that the electric motor power is larger, the gas turbine power and mass are significantly lower for the
constant gas turbine power operating mode (Figure 4.16).
All the previously mentioned effects appear to (partially) offset each other, and as a consequence, the MTOM of both operating modes is very similar (Figure 4.17). It might be the case that
for some supplied power ratio’s the MTOM of the constant gas turbine operating mode is slightly
lower, however the used weight estimations are not accurate enough to conclude anything in this
regard.
Ultimately, it can be concluded that the constant power operating mode results in a slightly
more optimal design with less fuel mass for approximately the same battery mass and MTOM. It is
important to note that, for most supplied power ratio’s, a certain power split can be chosen such that
the resulting design is exactly the same as the one found by using the constant gas turbine power
operating mode. Whether there is a certain combination of power splits that results in an even more
optimal design is investigated in the next section.
4.2. H YBRID A IRCRAFT
71
2,000
1,800
1,600
Fuel Mass [kg]
1,400
1,200
1,000
800
600
Power split op. mode (e bat = 1500 Wh/kg)
Constant P g ast ur b op. mode (e bat = 1500 Wh/kg)
Power split op. mode (e bat = 1000 Wh/kg)
Constant P g ast ur b op. mode (e bat = 1000 Wh/kg)
Power split op. mode (e bat = 750 Wh/kg)
Constant P g ast ur b op. mode (e bat = 750 Wh/kg)
400
200
0
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Supplied Power Ratio [-]
Figure 4.13: Difference in fuel mass for the constant gas turbine power operating mode compared to the power split
operating mode using a battery specific energy of 750, 1000 and 1500 Wh/kg
1.2
·104
Power split op. mode (e bat = 1500 Wh/kg)
Constant P g ast ur b op. mode (e bat = 1500 Wh/kg)
Power split op. mode (e bat = 1000 Wh/kg)
Constant P g ast ur b op. mode (e bat = 1000 Wh/kg)
Power split op. mode (e bat = 750 Wh/kg)
Constant P g ast ur b op. mode (e bat = 750 Wh/kg)
Battery Mass [kg]
1
0.8
0.6
0.4
0.2
0
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Supplied Power Ratio [-]
Figure 4.14: Difference in battery mass for the constant gas turbine power operating mode compared to the power split
operating mode using a battery specific energy of 1000 and 1500 Wh/kg
72
4. R ESULTS
6
·106
Power split op. mode (e bat = 1500 Wh/kg)
Constant P g ast ur b op. mode (e bat = 1500 Wh/kg)
Power split op. mode (e bat = 1000 Wh/kg)
Constant P g ast ur b op. mode (e bat = 1000 Wh/kg)
Power split op. mode (e bat = 750 Wh/kg)
Constant P g ast ur b op. mode (e bat = 750 Wh/kg)
Maximum P em [W]
5
4
3
2
1
0
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Supplied Power Ratio [-]
Figure 4.15: Difference in maximum electric motor power for the constant gas turbine power operating mode compared
to the power split operating mode using a battery specific energy of 750, 1000 and 1500 Wh/kg
1,000
900
Gas Turbine Mass [kg]
800
700
600
500
400
300
Power split op. mode (e bat = 1500 Wh/kg)
Constant P g ast ur b op. mode (e bat = 1500 Wh/kg)
Power split op. mode (e bat = 1000 Wh/kg)
Constant P g ast ur b op. mode (e bat = 1000 Wh/kg)
Power split op. mode (e bat = 750 Wh/kg)
Constant P g ast ur b op. mode (e bat = 750 Wh/kg)
200
100
0
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Supplied Power Ratio [-]
Figure 4.16: Difference in gas turbine mass for the constant gas turbine power operating mode compared to the power
split operating mode using a battery specific energy of 750, 1000 and 1500 Wh/kg
4.2. H YBRID A IRCRAFT
4
·104
Power split op. mode (e bat = 1500 Wh/kg)
Constant P g ast ur b op. mode (e bat = 1500 Wh/kg)
Power split op. mode (e bat = 1000 Wh/kg)
Constant P g ast ur b op. mode (e bat = 1000 Wh/kg)
Power split op. mode (e bat = 750 Wh/kg)
Constant P g ast ur b op. mode (e bat = 750 Wh/kg)
3.8
3.6
3.4
MTOM [kg]
73
3.2
3
2.8
2.6
2.4
2.2
2
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Supplied Power Ratio [-]
Figure 4.17: Difference in MTOW for the constant gas turbine power operating mode compared to the power split operating mode using a battery specific energy of 750, 1000 and 1500 Wh/kg
74
4. R ESULTS
4.2.4. O PTIMAL P OWER S PLIT
The above results using the power split operating mode are all generated using a constant power
split over the entire mission. However, as one might imagine, this might not yield the most optimal
design. Christopher Perullo and Dimitri Mavris [4] found that, using model predictive control, the
optimum power split varies from around 0.8 at the start of the mission to 0 at the very end of the
mission, see Figure 4.18. This optimum power split results, according to them, in the largest range
for a given fuel mass, or the lowest fuel mass for a given range.
Figure 4.18: Optimum power split using model predictive control [4]
The reasoning behind this is that it is optimal to burn as much fuel in the beginning of the mission to achieve a lighter aircraft and use more batteries at the end of the mission which would than
require to deliver less power because of the lighter aircraft. This effect is even magnified when using
Lithium-air batteries because these batteries add mass during the course of their usage. To see if
this assertion is correct, a similar power split was used as input into the modified Initiator program.
Since all phases of the mission (apart from the cruise) can only have a constant power split, the exact variation as can be seen in Figure 4.18 can not be achieved using the current Initiator program.
However, an approximation was achieved, which can be seen in Figure 4.19. The deviation and
hold/loiter are also included since these mission phases have to be included when determining the
fuel and battery mass. However, as is made clear in the subsequent plots, the power split variation
shown in Figure 4.19 does not result in a more optimal design point than a constant power split.
This is partially due to the large power requirement of both the gas turbine and the electric motor.
Because multiple climb phases are included in the mission (first at the start of the mission and later
on during the deviation to a different airport) and the first climb phase requires mostly gas turbine
power and the second climb phase requires mostly electric motor power, both the gas turbine and
the electric motor power have to be sized much larger resulting in a heavier aircraft, offsetting any
benefit in aircraft mass that might result from burning more fuel in the beginning of the mission.
For this reason a second power split variation is also investigated, see Figure 4.20. Here, the power
requirement of the secondary climb phase (and subsequent flight phases) is mostly handled by the
gas turbine, eliminating the need for a much heavier electric motor. Note that the power split is 1
during the descent phase, since no power split is used during this flight phase. On the y-axis in Figure 4.19 and 4.20, the power split is not shown, but rather the parameter "1 - S" in order to conform
with the definition of power split as used by Perullo et al. in Figure 4.18.
In subsequent figures the green dots represent the power split variation defined in Figure 4.19
and the yellow dots the one defined in Figure 4.20. Which, from this point on, will be referred to as
"power split variation 1" and "power split variation 2" respectively. These figures are constructed us-
4.2. H YBRID A IRCRAFT
75
1
1 - S [-]
0.8
0.6
0.4
0.2
0
0
200
400
600
800 1,000 1,200 1,400 1,600 1,800 2,000
Range [km]
Figure 4.19: Optimum power split input variation 1
1
1 - S [-]
0.8
0.6
0.4
0.2
0
0
200
400
600
800 1,000 1,200 1,400 1,600 1,800 2,000
Range [km]
Figure 4.20: Optimum power split input variation 2
ing a battery specific energy of 1000 Wh/kg. However, these effects can also be observed regardless
of battery specific energy.
In Figure 4.21 it can be seen that neither power split variation result in a more optimal design
compared to a constant power split during the entire mission. Both the fuel and battery mass appear
to be slightly larger. One reason for this effect is illustrated in Figure 4.22. For power split variation 1,
there is a very large increase in both the electric motor mass (including secondary systems) and gas
turbine mass, due to the reasons explained previously. This results in a higher MTOM (Figure 4.23),
requiring more battery and fuel mass. For power split variation 2, the electric motor (and secondary
systems) is slightly lighter in comparison to using a constant power split, however, the gas turbine
mass is again larger. When combined this also leads to an increase in MTOM, thus an increase in
fuel and battery mass.
Notwithstanding, the above reasoning does not give the full picture: there is also a very important secondary effect at play that explains why these power split variation are not optimal. Because
the gas turbine has to be sized quite large in order to meet the power requirements for the climb and
take-off phase, and later on in the mission the gas turbine power requirement is much smaller, the
SFC will keep increasing during the mission since the power setting will decrease 6 . This effect will
be less for power split variation 2 due to the larger power setting in the deviation and loiter flight
phases.
Overall it is clear that Perullo et al. [4] did not take into account several effects which have a very
large impacts on the design resulting in their optimal power split not resulting in an optimal design.
6 And small power settings result in high SFC, see Figure 3.7.
76
4. R ESULTS
The assumption made by Perullo et al. of having no increase in empty mass for a hybrid-electric
aircraft is an oversimplification which results in several effects being ignored.
Battery mass
Fuel mass
8,000
Mass [kg]
6,000
4,000
2,000
0
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Supplied Power Ratio [-]
Figure 4.21: Fuel and battery mass vs supplied power ratio for designs with constant power split and the optimum power
split according the Perullo et al.
1,400
Electric motor + wiring + inverter + battery cooling mass
Gas turbine mass
1,200
Mass [kg]
1,000
800
600
400
200
0
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Supplied Power Ratio [-]
Figure 4.22: Fuel and battery mass vs supplied power ratio for designs with constant power split and the optimum power
split according the Perullo et al.
4.3. S ENSITIVITY A NALYSIS
3.4
77
·104
3.2
MTOM [kg]
3
2.8
2.6
2.4
2.2
2
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Supplied Power Ratio [-]
Figure 4.23: MTOW vs supplied power ratio for designs with constant power split and the optimum power split according
the Perullo et al.
4.3. S ENSITIVITY A NALYSIS
In this section a sensitivity analysis is performed for range and battery specific energy. It is chosen
to investigate the effect an increase in range (compared to the reference aircraft) has on the feasibility and benefit of a hybrid-electric aircraft in order to get a better understanding of what type of
mission a hybrid-electric aircraft could perform. Since the battery specific energy has a very large
influence on the design (as is evident from the previously presented results) and the expected specific energy can not be predicted accurately, the influence of this parameter is investigated further.
One could also perform a sensitivity analysis for other parameters such as the power density of the
electric motor (or other components), however, the effect of these parameters on the design are very
predictable. For example decreasing the electric motor power density will result in a slightly heavier
design an as a result a slightly higher fuel and battery mass.
4.3.1. R ANGE
Figure 4.24 shows the variation of fuel mass with supplied power ratio for multiple mission ranges.
This plot shows that the benefit in terms of fuel mass of having a hybrid-electric aircraft diminishes
with an increase in range. For a range of more than 5000 km there appears to be no benefit at all. This
is because the larger the range, the larger the increase in MTOM with supplied power ratio (Figure
4.25). After a certain point, the increase in MTOM of a hybrid-electric aircraft results in such a large
increase in the total mission energy requirement that there is an increase in fuel requirement for the
mission compared to having a non-hybrid aircraft. When looking at Figure 4.24 there appears to be
an optimum of the supplied power ratio for a range of 5000 km. This is not the case for lower ranges,
an increase in supplied power ratio will always lead to a decrease in fuel mass. The reason for this
optimum is that when the supplied power ratio becomes too large, adding batteries will increase
the total energy requirement by an amount that is higher than the energy the batteries can deliver.
i.e. it takes more energy to transport the batteries than the energy the batteries can deliver.
78
4. R ESULTS
6,000
Range = 1528 km
Range = 3000 km
Range = 4000 km
Range = 5000 km
Fuel weight [kg]
5,000
4,000
3,000
2,000
1,000
0
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Supplied Power Ratio [-]
Figure 4.24: Variation of fuel mass with supplied power ratio for multiple ranges
4
·104
Range = 1528 km
Range = 3000 km
Range = 4000 km
Range = 5000 km
MTOW [kg]
3.5
3
2.5
2
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Supplied Power Ratio [-]
Figure 4.25: Variation of maximum take-off mass with supplied power ratio for multiple ranges
0.9
1
4.4. F INAL D ESIGN
79
4.3.2. B ATTERY SPECIFIC ENERGY
Figure 4.26 shows the variation in fuel mass with the battery specific energy for a multitude of supplied power ratio’s (Φ). As can be seen, the decrease in fuel mass between 750 and 1000 Wh/kg is
larger than the decrease between 1000 and 1500 Wh/kg, especially for larger supplied power ratios.
Obviously, for Φ = 0.0, the data is just a flat line. The difference between this line and the fuel mass
for the reference aircraft is due to the different configuration resulting in a slightly lower fuel mass.
2,200
Fuel Mass [kg]
↓ Reference aircraft fuel weight
2,000
Φ = 0.0
1,800
Φ = 0.1
Φ = 0.2
1,600
Φ = 0.3
1,400
Φ = 0.4
1,200
Φ = 0.5
Φ = 0.6
1,000
800
700
800
900
1,000
1,100
1,200
1,300
1,400
1,500
h
e bat [ W
kg ]
Figure 4.26: Fuel mass vs battery specific energy for multiple supplied power ratios
4.4. F INAL D ESIGN
Now that the design space is explored, one particular design will be examined further. First a design
point has to be chosen. The requirements (such as range) are the same as for the reference aircraft
in order to be able to make a comparison between the two, for the values, see Table 4.1. The two parameters that have the most influence on the design are the battery specific energy and the supplied
power ratio (i.e. how hybrid the aircraft is), see section 4.2.2. From literature it was found that a battery specific energy between 750 kW/kg and 1500 kW/kg can be expected from lithium-air batteries
by the year 2035. As was observed in Section 4.3 the benefit of increasing the specific energy from
750 Wh/kg to 1000 Wh/kg is larger than the benefit of increasing it from 1000 Wh/kg to 1500 Wh/kg.
Based on this observation, and the decrease in risk of choosing a relatively low specific energy, a
battery specific energy of 1000 Wh/kg is chosen for the design considered here.
A certain degree of hybridization or supplied power ratio has to be chosen as well. Several factors
have to be taken into account when selecting a certain value. First of all, the design should be
feasible. Choosing a too low supplied power ratio can result in a unstable aircraft since the center
of gravity can move too far to the rear because of the low battery mass. A too high supplied power
ratio on the other hand could result either in an infeasible design or in a design where the center
of gravity is moved too far to the front due to the large battery mass. For the chosen configuration
and a battery specific energy of 1000 Wh/kg a supplied power ratio between approximately 0.3 and
0.65 results in a feasible design with no stability problems. Another aspect that has to be accounted
for is the increase in cost with an increase in supplied power ratio. Since the cost is not calculated,
the MTOM is taken as a metric of "cost". Because the MTOM increases rapidly with supplied power
ratio, the supplied power ratio has to be taken as low as possible to keep the cost low. Of course, the
whole point of designing a hybrid electric aircraft is to reduce the fuel mass as much as possible,
80
4. R ESULTS
thus requiring a supplied power ratio that is as large as possible. It is the authors opinion that a
supplied power ratio of around 0.35 provides an adequate balance between all those factors.
As was concluded from section 4.2.3 the constant gas turbine operating modes result in a design
with slightly less fuel mass for about the same battery mass, MTOM and supplied power ratio compared to a constant power split operating mode. Thus a more optimal design, and, since no optimal
variable power split was found (Section 4.2.4), the constant gas turbine power operating mode is
chosen for the design discussed here.
Taking all of the above into account a battery specific energy of 1000 Wh/kg was chosen as well
as a constant maximum gas turbine power of 2.2 MW, resulting in a supplied power ratio of approximately 0.34. Table 4.4 shows the comparison of the chosen design with the reference aircraft in
terms of mass breakdown and some performance parameters. The climb rate shown is the maximum climb rate that occurs during the mission, and not necessarily the maximum achievable climb
rate.
Table 4.4: Parameters comparing the hybrid-electric aircraft to the reference aircraft
Parameter
Reference aircraft
Max take-off mass
[kg]
Mission fuel mass [kg]
Battery mass [kg]
Empty mass [kg]
Maximum
mission
climb rate [m/s]
Total mission energy
[MWh]
22340
Hybrid-electric
craft
25470
2050
0
12780
10.3
1470
2948
13552
7.2
– 28 %
n/a
+6%
– 29 %
26.19
21.73
– 17 %
air-
Difference
+ 14 %
As can be seen in the above table, using this hybrid-electric design results in an estimated 28 %
decrease in fuel mass compared to the reference aircraft at the cost of a 14 % increase in MTOM. This
increase in MTOM is largely due to the added battery mass, but also due to the increase in empty
mass. This increase in empty mass is not only due to the added electric motor, wiring, inverter and
battery cooling mass but also due to the increase in needed structural mass caused by the increase
in MTOM.
In figure 4.5 some basic geometrical parameters of the hybrid-electric aircraft are shown and
compared to the reference aircraft. The wings are obviously larger due to the increase in MTOM.
Figure 4.27 to 4.30 show the geometry of the hybrid-electric aircraft with the approximate size and
location of the power plant components.
Table 4.5: Parameters comparing the geometry of the hybrid-electric aircraft to the reference aircraft
Parameter
Reference aircraft
Wing span [m]
Wing area [m 2 ]
Fuselage length [m]
26.5
58.54
27
Hybrid-electric
craft
28.8
69.1
27.1
air-
Difference
+ 8.7 %
+ 18 %
+ 0.4 %
4.4. F INAL D ESIGN
81
8
6
4
2
25
20
10
5
15
0
10
−5
Figure 4.27: Isometric view of the hybrid-electric aircraft
Figure 4.28: Front view of the hybrid-electric aircraft
Figure 4.29: Side view of the hybrid-electric aircraft
−10
5
82
Figure 4.30: Top view of the hybrid-electric aircraft
4. R ESULTS
5
C ONCLUSION & R ECOMMENDATIONS
5.1. C ONCLUSION
The aim of this project is to investigate the possible advantage of a hybrid-electric aircraft concept
compared to a conventional aircraft for the year 2035. Since much uncertainty exists pertaining
to the expected level of technological development between now and 2035, many designs are investigated with multiple input parameters, in particular the effect of the battery specific energy is
investigated as well as the supplied power ratio. It is found that, for a range of 1528 km, the fuel
weight decreases with an increasing supplied power ratio, for any battery specific energy between
750 Wh/kg and 1500 Wh/kg. At the same time, the MTOM increases. This holds true for a range up
to around 5000 km (depending on the chosen battery specific energy), after which, either no benefit can be achieved from using a hybrid-electric aircraft or there exists an optimum in the supplied
power ratio. This is because, after a certain point, more energy is required to transport the batteries than the energy stored in the batteries itself. There is also a limit to the maximum achievable
supplied power ratio for most battery specific energy/range combinations. After a certain point the
MTOM (and thus also the energy requirement) increases to such a level that no more feasible design
is possible.
Two different operating modes are implemented: the power split operating mode and the constant gas turbine power operating mode. When comparing the power split operating mode, using
a constant power split, to the constant gas turbine power operating mode, it is found that the latter
generally results in a design with a lower mission fuel weight for approximately the same battery
weight and MTOM, while using the exact same inputs and having the same supplied power ratio.
Hence, resulting in a slightly more optimal design.
Of course, using a constant power split over the entire mission might not be optimal, and as
such it is investigated whether there is an optimal power split variation. Perullo et al. suggest using
a power split that decreases over the course of the mission (the aircraft uses more electrical energy
the further in the mission). It was found that this power split variation is not optimal because of
the resulting increase in gas turbine -, electric motor -, wiring - and battery cooling weight. Another
disadvantage of this power split variation is the increase in SFC. At this time, no optimal power split
is found.
Taking all these aspects into account one final design is considered using the constant gas turbine power operating mode with a battery specific energy of 1000 Wh/kg and a supplied power ratio
of 0.34. This feasible design results in a fuel weight reduction of approximately 28 %, and an increase in MTOM of 14 %. From this it can be concluded that there is definitely the possibility of
drastic fuel weight reduction by using the hybrid-electric aircraft concept (up to about 30 %), provided that there is sufficient technological progress between now and 2035, particularly pertaining
to battery specific energy density.
83
84
5. C ONCLUSION & R ECOMMENDATIONS
When designing a hybrid-electric aircraft, great care has to be taken in selecting not only a suitable power train architecture, but also an operating mode. These basic choices have to be taken into
account from the very start of the design process since they can have a very large impact on the final
design.
5.2. R ECOMMENDATIONS
There are some improvements which can be made in terms of the Initiator program itself, in order
to get more reliable, accurate results. First of all the model of the power and fuel consumption variation with speed, altitude and power setting can be improved. At the moment it is only valid for one
specific engine (PW 124B), and it is assumed all other engines show the exact same behaviour. The
program is also limited to the parallel-hybrid power train. It could be expanded relatively easily to
also include the series-hybrid architecture such that the user can select the appropriate architecture. A comparison between those two (or more) architectures can also be made.
Currently, only a constant power split can be selected for all flight phases apart from the cruise
phase. It could be that that simplification results in non-optimal designs. As such, being able to
input a variable power split over the entire mission or a power split curve (such as constructed by
Perullo et al., see Figure 4.18) might provide better results.
During descent it is chosen to keep the gas turbine at idle while the electric motor is switched
off. Since the electric motor does not need to spool up, it could, in theory, be possible to switch
the gas turbine completely off when the available electric motor power is relatively large. A further
study could determine the optimal strategy that can be used during descent, taking into account
any applicable regulations.
The method for determining the battery cooling mass is very limited and most likely not very
accurate. A more detailed design study of a hybrid-electric aircraft will have to incorporate a better
method for sizing the battery cooling.
No class 1 sizing method for hybrid-electric aircraft is implemented and the class 2 method
gives large errors in some cases (especially when using the constant gas-turbine operating mode).
For this reason the time to converge for a hybrid-electric aircraft design is sometimes much longer
compared to a conventional design. Implementing a class 1 sizing method and updating the class
2 method might improve this drastically, although it will make no difference to the ultimate design.
In order to further reduce the computational time required, some more general optimization is also
possible, especially in the mission analysis.
Since the power plant is such an important aspect of a hybrid-electric aircraft, a more detailed
study of the power plant should be done. This would paint a better picture of the challenges, opportunities and limitations of such a power plant for aerospace applications. It could also aid in
producing a more detailed sizing method.
The used configuration for all hybrid-electric designs is based upon the Euroflyer [1]. This configuration also incorporates boundary layer ingestion and contra-rotating propellers. The benefits
(and challenges) these aspects can provide are not taken into account. Adding parts to the Initiator
which are able to compute the effects of the boundary layer ingestion and contra-rotating propellers
would take quite some time, however it would be interesting to find out how much benefit can be
achieved from this configuration.
As is discussed in Section 4.2.4 no optimal split variation has been found so far. It would be
an interesting study to attempt to find such an optimum. This would most likely include an optimization, however, since one design iteration can easily take more than 30 minutes, either a lot of
computational power is required, or some more optimization of the code has to occur.
A
D ERIVATION OF HYBRID - ELECTRIC RANGE
EQUATION
The range is obtained from the following definite integral:
t2
Z
V dt
(A.1)
t1
using
dE
= P bat + P f uel
dt
(A.2)
Equation A.1 becomes:
Z
R=
E st ar t
Z
=
E f i nal
E st ar t
E f i nal
−
V
dE
P bat + P f uel
V
dE
P bat + P f uel
(A.3)
Using
P f uel = P g ast ur b ∗ SFC ∗ e f uel
= P sha f t ∗ (1 − S) ∗ SFC ∗ e f uel
And
P bat =
S ∗ P sha f t
η el
(A.4)
(A.5)
The factor the range becomes:
Z
R=
E st ar t
E f i nal
V
³
S
η el
´
dE
+ (1 − S) ∗ SFC ∗ e f uel ∗ P sha f t
(A.6)
During the cruise phase P sha f t is equal to:
P sha f t =
D ∗V
η pr op
(A.7)
And
D=
CD
∗W
CL
85
(A.8)
86
A. D ERIVATION OF HYBRID - ELECTRIC RANGE EQUATION
So
V
P sha f t
becomes:
V
P sha f t
=
C L η pr op
∗
CD
W
(A.9)
As such, Equation A.6 becomes:
R=
1
S
η el
+ (1 − S) ∗ SFC ∗ e f uel
CL
∗ η pr op ∗
CD
∗
Z
E st ar t
E f i nal
1
dE
W
(A.10)
Now we write the weight as a function of energy:
W = Wempt y + Wbat + W f uel
= Wempt y +
= Wempt y +
Now we introduce x =
E bat
E t ot .
E bat E f uel
+
e bat e f uel
E bat ∗ e f uel + E f uel ∗ e bat
(A.11)
e f uel ∗ e bat
So for S=1, x = 1 and for S=0, x=0:
E bat
E t ot
E bat
=
E bat + E f uel
x=
=
Using S =
(A.12)
E em
η el
E em
η el
+ E g ast ur b ∗ SFC ∗ e f uel
E em
E sha f t :
S ∗ E sha f t
x=
S ∗ E sha f t + (1 − S) ∗ E sha f t ∗ SFC ∗ e f uel ∗ η el
S
=
S + (1 − S) ∗ SFC ∗ e f uel ∗ η el
With x =
E bat
E t ot
(A.13)
Equation A.11 becomes:
W = Wempt y + E
x ∗ e f uel + (1 − x) ∗ e bat
e f uel ∗ e bat
(A.14)
x∗e f uel +(1−x)∗e bat
The factor
(with x being defined in Equation A.13) can be seen as the combined
e f uel ∗e bat
specific energy of the batteries and fuel. From now on this factor will be written as e combi ned . As
such, the range equation (Equation A.10) becomes:
R=
1
S
η el
+ (1 − S) ∗ SFC ∗ e f uel
∗
CL
∗ η pr op ∗
CD
Z
E st ar t
E f i nal
1
dE
Wempt y + E ∗ e combi ned
(A.15)
Since e combi ned is constant for S = constant:
R=
1
S
η el
+ (1 − S) ∗ SFC ∗ e f uel
µ
¶
e combi ned ∗ E st ar t + Wempt y
CL
1
∗
∗ln
∗ η pr op ∗
(A.16)
CD
e combi ned
Wempt y
B IBLIOGRAPHY
[1] S. Bosma, A. Eggermont, R. Heuijerjans, F. Kruijssen, S. Leest, M. Meijburg, K. Morias, F. v. d.
Oudenalder, B. Peerlings, and K. v. Zomeren, Euroflyer - an environmentally friendly regional
aircraft with a propulsive fuselage entering into service in 2035, Design Synthesis Exercise 2013
- Delft University of Technology (2013).
[2] R. Schiferl, A. Flory, W. C. Livoti, and S. D. Umans, High-temperature superconducting synchronous motors: Economic issues for industrial applications, IEEE Transactions on Industry
Applications 44, 1376 (2008), cited By :11 Export Date: 8 January 2015.
[3] Performance model Fokker 50, Report (Delft University of Technology, 2010).
[4] C. Perullo and D. Mavris, A review of hybrid-electric energy management and its inclusion in
vehicle sizing, Aircraft Engineering and Aerospace Technology 86, 550 (2014).
[5] Advisory Council for Aviation Research and Innovation in Europe (ACARE), , Realising europe’s
vision for aviation, Strategic Research and Innovation Agenda 1 (2012).
[6] National Aeronautics and Space Administration, , Advanced concept studies for subsonic and
supersonic commercial transport entering service in 2030-35 period, NASA Research Announcement, Pre-Proposal Conference (2007).
[7] M. K. Bradley and C. K. Droney, Subsonic ulta green aircraft research phase ii n+4 advanced
concept development, NASA report NNL08AA16B (2012).
[8] S. Bruner, S. Baber, C. Harris, N. Caldwell, P. Keding, K. Rahrig, and L. Pho, Nasa n+3 subsonic
fixed wing silent efficient low-emissions commercial transport (select) vehicle study, NASA report
NNC08CA86C (2010).
[9] M. K. Bradley and C. K. Droney, Subsonic ultra green aircraft research: Phase 1 final report,
Boeing Research & Technology, Huntington Beach, California (2011).
[10] C. Pornet, C. Gologan, P. C. Vratny, A. Seitz, O. Schmitz, A. T. Isikveren, and M. Hornung,
Methodology for sizing and performance assessment of hybrid energy aircraft, Journal of Aircraft
, 1 (2014).
[11] G. E. Bona, M. Bucari, A. Castagnoli, and L. Trainelli, Flybrid: Envisaging the future hybridpowered regional aviation, (2014), 10.2514/6.2014-2733.
[12] F. Christian and A. R. Paul, Design of hybrid-electric propulsion systems for light aircraft, in 14th
AIAA Aviation Technology, Integration, and Operations Conference, AIAA Aviation (American
Institute of Aeronautics and Astronautics, 2014) doi:10.2514/6.2014-3008.
[13] C. C. Chan, A. Bouscayrol, and K. Chen, Electric, hybrid, and fuel-cell vehicles: Architectures
and modeling, Vehicular Technology, IEEE Transactions on 59, 589 (2010).
[14] S. J. Gerssen-Gondelach and A. P. C. Faaij, Performance of batteries for electric vehicles on short
and longer term, Journal of Power Sources 212, 111 (2012).
87
88
B IBLIOGRAPHY
[15] B. Scrosati and J. Garche, Lithium batteries: Status, prospects and future, Journal of Power
Sources 195, 2419 (2010).
[16] M. Millikin, Envia systems hits 400 wh/kg target with li-ion cells; could lower li-ion cost to
$180/kwh, Green Car Congress (2012).
[17] L. F. Nazar, M. Cuisinier, and Q. Pang, Lithium-sulfur batteries, MRS Bulletin 39, 436 (2014).
[18] B. Scrosati, J. Hassoun, and Y. K. Sun, Lithium-ion batteries. a look into the future, Energy &
Environmental Science 4, 3287 (2011).
[19] S. Stuckl, J. v. Toor, and H. Lobentanzer, Voltair - the all electric propulsion concept platform - a
vision for atmospheric friendly flight, 28th international congress of the aeronautical sciences
(2012).
[20] M.-K. Song, Y. Zhang, and E. J. Cairns, A long-life, high-rate lithium/sulfur cell: A multifaceted
approach to enhancing cell performance, Nano Letters 13, 5891 (2013).
[21] Y. Mikhaylik, I. Kovalev, R. Schock, K. Kumaresan, J. Xu, and J. Affinito, High energy rechargeable
li-s cells for ev application. status, challenges and solutions, Sion Power Corporation (2010).
[22] G. Girishkumar, B. McCloskey, A. C. Luntz, S. Swanson, and W. Wilcke, Lithium-air battery:
Promise and challenges, The Journal of Physical Chemistry (2010), 10.1021/jz1005384|J.
[23] K. Alexander and Y. Ein-Eli, Review on li–air batteries—opportunities, limitations and perspective, Journal of Power Sources 196, 886 (2011).
[24] H. Kuhn, A. Seitz, L. Lorenz, A. Isikveren, and A. Sizmann, Progress and perspectives of electric
air transport, 28th International congress of the aeronautical sciences (2012).
[25] H. Kuhn and A. Sizmann, Fundamental prerequisites for electric flying, Deutscher Luft- und
Raumfahrtkongress 2012 (2012).
[26] L. Johnson, The viability of high specific energy lithium air batteries, Symposium on Research
Opportunities in Electrochemical Energy Storage - Beyond Lithium Ion: Materials Perspectives
(2010).
[27] K. Rajashekara, Present status and future trends in electric vehicle propulsion technologies, Journal of emerging and selected topics in power electronics 1 (2013).
[28] S. W. Ashcraft, A. S. Padron, K. A. Pascioni, and G. W. Stout, Review of propulsion technologies
for n+3 subsonic vehicle concepts, NASA report (2011).
[29] J. C. Mankins, Technology readiness levels: A white paper, NASA (1995).
[30] P. J. Masson and C. A. Luongo, High power density superconducting motor for all-electric aircraft
propulsion, Applied Superconductivity, IEEE Transactions on 15, 2226 (2005).
[31] C. A. Luongo, P. J. Masson, T. Nam, D. Mavris, H. D. Kim, G. V. Brown, M. Waters, and D. Hall,
Next generation more-electric aircraft: A potential application for hts superconductors, Applied
Superconductivity, IEEE Transactions on 19, 1055 (2009).
[32] M. J. Gouge, J. A. Demko, and B. W. McConnell, Cryogenics assessment report, Oak Ridge National Laboratory (2002).
B IBLIOGRAPHY
89
[33] K. T. Chau and Y. S. Wong, Overview of power management in hybrid electric vehicles, Energy
Conversion and Management 43, 1953 (2002).
[34] K. Çağatay Bayindir, M. A. Gözüküçük, and A. Teke, A comprehensive overview of hybrid electric
vehicle: Powertrain configurations, powertrain control techniques and electronic control units,
Energy Conversion and Management 52, 1305 (2011).
[35] J. Y. Hung and L. F. Gonzalez, On parallel hybrid-electric propulsion system for unmanned aerial
vehicles, Progress in Aerospace Sciences 51, 1 (2012).
[36] European Aviation Safety Agency, , Certification specifications for large aeroplanes cs-25,
(2007).
[37] Federal Aviation Administration, , Requisitos federal aviation regulations: Part 25 - airworthiness standards: Transport category airplanes, ().
[38] F. Christian and P. Robertson, Hybrid-electric propulsion for automotive and aviation applications, CEAS Aeronautical Journal , 1 (2014).
[39] J. A. Rosero, J. A. Ortega, E. Aldabas, and L. Romeral, Moving towards a more electric aircraft,
Aerospace and Electronic Systems Magazine, IEEE 22, 3 (2007).
[40] H. Zhang, C. Saudemont, B. Robyns, and M. Petit, Comparison of technical features between a
more electric aircraft and a hybrid electric vehicle, in Vehicle Power and Propulsion Conference,
2008. VPPC ’08. IEEE, pp. 1–6.
[41] R. Singh, A. T. Isikveren, S. Kaiser, C. Pornet, and P. C. Vratny, Pre-design strategies and sizing techniques for dual-energy aircraft, Aircraft Engineering and Aerospace Technology 86, 525
(2014).
[42] M. Hoogreef, Aircraft initiator manual, .
[43] MathWorks® , Matlab, (http://nl.mathworks.com/products/matlab/).
[44] D. P. Raymer, Aircraft Design: A conceptual Approach (American Institure of Aeronautics and
Astronautics (AIAA), 1992).
[45] J. Roskam, Airplane Design Part II: Preliminary Configuration Design and Integration of the
Propulsion System (2013).
[46] J. Ruijgrok, Elements of airplane performance, 2nd ed. (VSSD, Delft, 2009).
[47] B. Gerald, Weights and efficiencies of electric components of a turboelectric aircraft propulsion system, in 49th AIAA Aerospace Sciences Meeting including the New Horizons Forum and
Aerospace Exposition, Aerospace Sciences Meetings (American Institute of Aeronautics and Astronautics, 2011) doi:10.2514/6.2011-225.
[48] Synergy Cables Ltd., , Dataset of medium voltage power cables, (2015).
[49] M. J. Hennessy, Lightweight, Efficient Power Converters for Advanced Turboelectric Aircraft
Propulsion Systems, Report (NASA, 2014).
[50] Federal Aviation Administration, , Part 23 – airworthiness standards: Normal, utility, acrobatic
and commuter airplanes, ().
Was this manual useful for you? yes no
Thank you for your participation!

* Your assessment is very important for improving the work of artificial intelligence, which forms the content of this project

Download PDF

advertisement