A GENERIC BENCHMARK FOR A MINI

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A GENERIC BENCHMARK FOR A MINISPLIT HEAT PUMP SYSTEM
Yuchen Wang
University of Nebraska-Lincoln, ywang01@unomaha.edu
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A GENERIC BENCHMARK FOR A MINI-SPLIT HEAT PUMP SYSTEM
BY
Yuchen Wang
A THESIS
Presented to the Faculty of
The Graduate College at the University of Nebraska
In Partial Fulfillment of Requirements
For the Degree of Master of Science
Major: Architectural Engineering
Under the Supervision of Professor Haorong Li
Lincoln, Nebraska
December 2016
A GENERICAL BENCHMARK FOR MINI-SPLIT HEAT PUMP SYSTEM
YUCHEN WANG, M.S.
University of Nebraska, 2016
Advisor: Haorong Li
Heating, Ventilation, and Air Conditioning (HVAC) accounts for half of the
building energy consumption in the U.S where Mini-Split Heat Pumps (MSHPs) are an
emerging type of HVAC system. Their utilization has greatly increased by 34% from
2009 to 2013 and high potential EER is recognized for MSHPs. However, there is limited
research involving MSHPs systems, and there is no generic benchmark for system testing
and modeling. The available simulation tools such as VapCyc, GreatLab, and CYCLE_D
are either too complicated, difficult to access, or not freely available. Therefore, an
accurate and public share generic benchmark is essential and will be researched for
researchers and scientists.
In this study, the Heat Pump Design Model (HPDM) is utilized to investigate
MSHP performance values. There are five different kinds of input parameters necessary
for the HPDM, namely a general system description, system refrigerant-side balancing,
compressor characteristics which need a compressor scaling method, fin-and-tube heat
exchanger parameters, and system operating conditions. Based on systematic inputs of
the HPDM, several key outputs can be obtained, including system capacity, power
consumption, and mass flow rate. By comparing output values with existing data sets, the
capability of a generic model for MSHP can be identified.
In order to validate the methodology analyzed above, two kinds of case studies
will be presented. In the first study, a comparison of lab data and simulation results is
presented, whereas in the second one, a comparison is conducted between manufacturing
data and simulation results. By identifying all of the input parameters for the specified
unit, which is the LG LA096HV in this study, the HPDM can obtain simulation results
immediately. As indicated by simulation results, the HPDM can be a generic benchmark
in a certain temperature range with a relative error below 5%.
IV
ACKNOWLEDGEMENT
I would like to express my gratitude to my supervisor, Dr. Haorong Li. With his
selfless and valuable help, I can develop my thesis at a high level. Not only would he
help me in my thesis organization details, but also he introduced several really helpful
people. I also would like to extend my greatest sincere gratitude to Dr. Bo Shen who was
introduced by Dr. Haorong Li. He is a really kind and nice man who is a research and
development scientist at the Oak Ridge National Lab. When I have several problems with
the thesis or the questions for the Heat Pump Design Model, he always helps me answer
my questions without any doubts. In addition, I am grateful to Dr. David Yuill and Dr.
Howard Cheung. Thanks to their great efforts for providing the lab data, I could finish
one of the case studies mentioned in my thesis. Moreover, they both are very kind and
professional researchers since they can help solving my problem sincerely. Also, I want
thank all my committee members again. In addition, I would like to thank all my
colleagues: Krittima Santiwattana, Sungmin Yoon, Mohd Eslam Dahdolan, and Ling Li.
All of them help me with their best efforts.
Finally, I would like to thank my parents, for their endless encouragement, love,
and support.
V
VI
TABLE OF CONTENTS
Chapter 1.
INTRODUCTION ...................................................................................... 16
1.1.
Background ........................................................................................................ 16
1.2.
Literature Review ............................................................................................... 20
1.3.
Motivation and Objectives ................................................................................. 24
1.4.
Methodology ...................................................................................................... 25
1.5.
Thesis Organization............................................................................................ 25
Chapter 2.
Data Sources ............................................................................................... 26
2.1.
Overview ............................................................................................................ 26
2.2.
Laboratory Data.................................................................................................. 26
2.3.
Manufacturing Data............................................................................................ 27
Chapter 3.
DOE/ORNL Heat Pump Design Model ...................................................... 30
3.1. Introduction to the Heat Pump Design Model .................................................... 30
3.2. Methodology of Heat Pump Design Model ........................................................ 33
Chapter 4.
A Generic benchmark for Mini-Split Heat Pump System .......................... 69
4.1.
Overview ............................................................................................................ 69
4.2.
Case study 1: HPDM inputs for the lab data ...................................................... 69
4.3
Case study 2: HPDM inputs for the manufacturing data ................................... 76
4.4
Case study 1&2 results for laboratory and manufactural data by using HPDM 77
VII
Chapter 5.
Conclusions and future work ...................................................................... 97
List of References ........................................................................................................... 100
Appendix I Rotary Compressor Map with Rated Capacity as 7125 Btu/Hr ................... 104
Appendix II Rotary Compressor Map with Rated Capacity as 11740 Btu/hr ................ 106
Appendix III Rotary Compressor Map with Rated Capacity as 5300 Btu/hr ................. 108
Appendix IV Rotary Compressor Map with Rated Capacity as 9163 Btu/hr ................. 110
Appendix V Scroll Compressor Map with Rated Capacity as 28999 Btu/hr ................. 112
Appendix VI Scroll Compressor Map with Rated Capacity as 56898 Btu/hr ................ 114
Appendix VII laboratory data inputs for cooling modes ................................................ 116
Appendix VIII laboratory performance data sets for cooling modes ............................. 117
Appendix IX HPDM laboratory data outputs for cooling modes ................................... 118
Appendix X laboratory data inputs for heating modes ................................................... 119
Appendix XI laboratory performance data sets for heating modes ................................ 120
Appendix XII HPDM laboratory data outputs for heating modes .................................. 121
Appendix XIII HPDM manufactural data outputs for cooling modes ............................ 122
Appendix XIV HPDM manufactural data outputs for heating modes ............................ 123
Appendix XV lab data suction, discharge pressure and system charge for cooling mode
......................................................................................................................................... 124
Appendix XVI HPDM results lab data suction, discharge pressure and system charge for
cooling mode ................................................................................................................... 125
VIII
Appendix XVII lab data suction, discharge pressure and system charge for heating mode
......................................................................................................................................... 126
Appendix XVIII HPDM results lab data suction, discharge pressure and system charge
for heating mode ............................................................................................................. 127
IX
LIST OF TABLES
Table 2-1 Manufactural testing data for LG 096HV in the cooling mode ........................ 28
Table 2-2 Manufactural testing data for LG 096HV in the heating model ....................... 29
Table 3-1 Relative errors for power consumption prediction from 7125 Btu/hr to 11740
Btu/hr ................................................................................................................................ 48
Table 3-2 Relative errors for mass flow rate prediction from 7125 Btu/hr to 10150 Btu/hr
........................................................................................................................................... 49
Table 3-3 Relative errors for power consumption prediction from 7125 Btu/hr to 5300
Btu/hr ................................................................................................................................ 50
Table 3-4 Relative errors for mass flow rate prediction from 7125 Btu/hr to 5300 Btu/hr
........................................................................................................................................... 50
Table 3-5 Relative errors for power consumption prediction from 28999 Btu/hr to 56898
Btu/hr ................................................................................................................................ 52
Table 3-6 Relative errors for mass flow rate prediction from 28999 Btu/hr to 56898
Btu/hr ................................................................................................................................ 53
Table 4-1 Power consumption coefficients....................................................................... 72
Table 4-2 Mass flow rate coefficients ............................................................................... 72
Table 4-3 heat exchanger parameters for the indoor unit ................................................. 75
Table 4-4 heat exchanger parameters for the outdoor unit ............................................... 75
Table 4-5 the relative errors for lab data outputs in cooling mode ................................... 80
Table 4-6 Compressor suction, discharge pressure and system charge ............................ 84
Table 4-7 the relative error for lab data outputs in heating mode ..................................... 85
X
Table 4-8 Compressor suction, discharge pressure and system charge ............................ 86
Table 4-9 Capacity relative error for manufacture data in the cooling mode ................... 90
Table 4-10 Power consumption error for manufacture data in the cooling mode ............ 91
Table 4-11 Capacity and power consumption relative error for manufacture data in the
heating mode ..................................................................................................................... 94
XI
LIST OF FIGURES
Figure 1-1 Primary energy supply by fuels....................................................................... 17
Figure 1-2 Primary energy supply by regions................................................................... 17
Figure 1-3 Developed and developing countries’ energy consumption Source: Energy
Information Administration (EIA) .................................................................................... 17
Figure 1-4 GreatLab and its components .......................................................................... 22
Figure 3-1 The interface for the DOE/ORNL Heat Pump Design Model ........................ 31
Figure 3-2 Climate distributed zones in the U.S. .............................................................. 32
Figure 3-3 The interface of General System Description ................................................. 34
Figure 3-4 Three different ways to achieve system refrigerant-side balancing ................ 35
Figure 3-5 the logic diagram for specifying SH and SC ................................................... 36
Figure 3-6 the logic diagram for specifying SC and system refrigerant charge ............... 37
Figure 3-7 the logic diagram for specifying SH and system refrigerant charge ............... 38
Figure 3-8 The components of compressor characteristics............................................... 40
Figure 3-9 the interface for compressor selection............................................................. 41
Figure 3-10 the interface of compressor data ................................................................... 42
Figure 3-11 Ranges of capacity applications for different compressor types ................... 44
Figure 3-12 the AF for the rotary compressors examples................................................. 45
Figure 3-13 The AF for the scroll compressors example ................................................. 51
Figure 3-14 the interface for scaling compressor performance ........................................ 55
Figure 3-15 the interfaces for scaling system performance .............................................. 55
Figure 3-16 the interface of indoor unit heat exchanger configuration ............................ 56
Figure 3-17 the interface of outdoor unit heat exchanger configuration .......................... 57
XII
Figure 3-18 the geometry diagram of a tube ..................................................................... 58
Figure 3-19 a transverse figure for a heat exchanger ........................................................ 59
Figure 3-20 a 3D figure for a heat exchanger .................................................................. 60
Figure 3-21 the diagram for number of equivalent, parallel circuits for an evaporator .... 61
Figure 3-22 the diagram for number of equivalent, parallel circuits for an evaporator .... 62
Figure 3-23 Key points for a vapor compression cycle in a P-h diagram Source:(website
owner, 2016) ..................................................................................................................... 64
Figure 3-24 Printed results for system operating conditions and performance ................ 66
Figure 3-25 Printed results for component sizing and system charge .............................. 67
Figure 3-26 Detailed inputs and outputs for the HPDM ................................................... 68
Figure 4-1 The diagram power consumption linear regression ........................................ 73
Figure 4-2 The diagram for mass flow rate linear regression ........................................... 73
Figure 4-3 Cooling capacity comparison for lab data cooling mode ................................ 81
Figure 4-4 EER comparison for lab data cooling mode ................................................... 81
Figure 4-5 Mass flow rate comparison for lab data cooling mode ................................... 82
Figure 4-6 SHR comparison for lab data cooling mode ................................................... 82
Figure 4-7 Power consumption comparison for lab data cooling mode ........................... 83
Figure 4-8 Heating capacity comparison for lab data heating mode ................................ 88
Figure 4-9 COP comparison for lab data heating mode ................................................... 88
Figure 4-10 Power consumption comparison for lab data heating mode ......................... 89
Figure 4-11 Mass flow rate comparison for lab data heating mode ................................. 89
Figure 4-12 Cooling capacity comparison for manufactural data in the cooling mode .... 92
Figure 4-13 Power consumption comparison for manufactural data in the cooling mode 93
XIII
Figure 4-14 Heating capacity comparison for manufactural data in the heating mode .... 95
Figure 4-15 Power consumption comparison for manufactural data in the heating mode 96
XIV
NOMENCLATURE

outdoor dry bulb temperature

indoor dry bulb temperature

outdoor wet bulb temperature

indoor wet bulb temperature
P
finned face area
a
longitudinal center-to-center distance between tubes
b
transverse center-to-center distance between tubes
h
height for the heat exchanger
d
depth for this heat exchanger
#r
number of tubes in each row
#n
number of row
15
16
CHAPTER 1.
INTRODUCTION
1.1. Background
With the development of economy and society, energy consumption is increasing for
both developed and developing countries. During the years between 1984 and 2004, the
consumption of primary energy sources which include non-renewable energy and several
renewable energy sources from nature (WIKIPEDIA, 2016) increased by 43% (PérezLombard, Ortiz, & Pout, 2008). In addition, the trend of increasing energy consumption
will continue. The rapid speed of economic increase for developing countries is higher
than for developed countries, with 3.2% annual rate for emerging countries and 1.1%
annual rate for developed countries, separately (Pérez-Lombard et al., 2008). Oil, coal,
and natural gas combustion are in the primary consuming position (IEA, 2014) in the
year 2012, shown in Figure 1-1. As shown in Figure 1-2, the primary energy sources are
mainly exploited in the developed countries, but those energy sources are also applied
greatly in the developing nations, especially in China with 21.8% of the total energy
consumption.
According to the Energy Information Administration (EIA), the energy consumption
of emerging economies will surpass developed nations in 2020, shown in Figure 1-3.
Typically, energy consumption can be divided into three sectors: industry, transport and
other uses. Building energy consumption accounts for 40% for the total energy
17
consumption in the U.S. (Cho, Li, Park, & Zheng, 2015) and amounts to about 39
quadrillions Btu, a large amount of total energy consumption (EIA, 2016).
Figure 1-1 Primary energy supply by fuels
Figure 1-2 Primary energy supply by regions
Figure 1-3 Developed and developing countries’ energy consumption Source: Energy
Information Administration (EIA)
18
Heating, ventilation, and air conditioning (HVAC) systems play a significant role in
commercial and residential building energy consumption. According to data provided by
the U.S. EIA and European Commission in 2014, half of building energy consumption is
due to HVAC system operation (Knight, 2012) (U.S. EIA, 2014). Therefore, there is an
extremely necessary and valuable importance to investigate HVAC consumption
classification. Residential energy consumption (45% of the total) and commercial energy
consumption (55% of the total) are included in building energy consumption (U.S. DOE,
2011). The amount of cooling and ventilation energy usage is 16% for commercial
buildings while heating energy is 26%. In terms of residential energy consumption, 46%
is for heating, which is much higher than commercial building energy usage. Meanwhile,
9% is for cooling energy consumption, which is lower than commercial buildings
(Mitchell & Braun, 2011).
Typically, there are ducted systems and ductless systems utilized in buildings. Ducted
systems are most traditional systems in the United States, while ductless systems are
rather new in the U.S., though they have a large market share in Asian countries
(Carmichael, Bielecki, Meyer, & Salvador, 2015). Rooftop packaged units (RTUs) are
utilized in commercial buildings in the U.S., while Mini-Split systems are widely used in
residences, particularly in Asian countries. Moreover, the residential HVAC market is
increasing in the U.S., while the commercial HVAC market is expected to steadily grow
in the future (News, 2016). The Mini-Split Heat Pump (MSHP) system is a very highefficiency HVAC system and therefore its market share has a promising future, with only
5% of the total cooling and heating system market in the U.S. (Green Building Advisor,
2015). Additionally, the overall MSHP market increased between 2009 and 2013 by
19
34%(Navigant Consulting, 2014), which means that urgent research is required in the
residential HVAC market.
A trustworthy simulation model or benchmark can be incredibly prominent for
operation. An outstanding model could provide several advantages as follows:

Large savings on experimentation costs

Increased efficiency for testing unit performance

Undisturbed experimental conditions

Increased safety for difficult experiments (Ron, 2016).
In order to design higher efficiency residential HVAC systems, the simulation
software used for analysis and application should be based on an accurate model or
benchmark. There are many RTUs developed for researching performance in commercial
buildings. Also, there are many that investigate system simulation programs. For
example, Trane company investigates the TRACE 700 which is helpful for simulating
building energy consumption. EnergyPlus, funded by the U.S. Department of Energy
Building Technologies Office, is a whole-building energy simulation program for
modeling energy consumption applied in buildings due to cooling and heating depletion,
lighting, ventilation, and other loads. (U.S. DOE, 2015) Both types of software can
conduct reliable simulation processes.
For residential buildings, especially for mini-split systems, there are limited
researches about simulating the entire vapor compression cycle. Few software programs
can be achieved for this purpose. For instance, EES can simulate a refrigeration cycle
with its programming but it is time-consuming. Some well-known companies, like
20
Carrier and Danfoss, create databases for their customers. They can simulate refrigeration
cycles only within their own units or equipment.
It is clear that a generic benchmark for the mini-split system would be proposed of
great value. The Heat Pump Design Model (HPDM) developed by Oak Ridge National
Lab for the U.S. Department of Energy (DOE) has been widely used in the residential
building market, but only for split systems. Since the HPDM works well in split systems,
there is a possibility that it can simulate mini-split systems well also.
1.2. Literature Review
There are limited models and simulation software packages devoted to simulating a
mini-split heat pump refrigeration cycle. Some simulation programs focus on calculating
system loads and analyzing power consumption, for example, Trace 700 and EnergyPlus.
There are also some simulation models made by companies, for instance, Simtools, made
by Carrier, and T-Rex, created by Trane. But because of commercial confidentiality
agreements, those companies communicate with others rarely. (Chunlu, 2012) Some
programs, like Dymola, ASPEN, AMESim, and SimulationX, can make a simple
refrigeration cycle simulation, but they can only simulate uncomplicated refrigeration
components. For complex vapor compression cycles or modeling, the speed of simulation
processing will be slow and the simulation results will not be robust enough. Therefore,
these programs are not good at simulating complicated refrigeration cycles.
Richardson, et. al (2006) developed a component-based platform for simulations of
steady-state cycles at the Center for Environmental Energy Engineering (CEEE) at the
21
University of Maryland. Named VapCyc (Andresen, 2009), this software can achieve
more complex refrigeration cycle simulations and utilizes geometry input for processing.
It also calculates the charge inventory of the simulation cycle. Another combined
software also provided by the CEEE is Coil Designer, which is a sophisticated tool for
design and optimization of air-cooled heat exchangers (CEEE, 2016). It is a professional
and highly customizable software for designing heat exchangers using the tube-in-tube
method. When users finish their heat exchanger design, the VapCyc can be inputted
within geometry files engendered by Coil Designer. The VapCyc requires users to choose
individual component models (compressor, condenser, evaporator and expansion device
models) and a value for system refrigerant charge. Once those parameters are fixed, the
VapCyc executes vapor compression cycle simulation (Richardson & Jiang, 2002). The
main projects the the VapCyc model are rooftop units’ projects, especially for the
supermarket.
The National Institute of Standards and Technology (NIST) developed a basic
simulation software named CYCLE_D which focuses on vapor compression refrigeration
cycles using pure refrigerants or blends of refrigerants (Brown, Domanski, & Lemmon,
2009). It has been investigated for a long time and now there is a version 5.1 presented
for users. Not only can CYCLE_D simulate simple vapor compression cycles which
include one compressor, a condenser, an evaporator and an expansion device, but it can
also simulate subcritical cycles which may contain a second compressor, economizers or
an intercooler. Through great work done by NIST, the CYCLE_D has become an easy
and convenient program aiming for basic refrigeration cycle simulations, two-stage
economizer cycle, and three-stage economizer cycle simulations. Additionally, the
22
program can generate simulation results on P-h state diagram and T-s state diagram. One
more advantage is that the compressor model can be represented as a 10-coefficient
formula based on ARI Standard 540-2004. However, users may not select their individual
heat exchanger geometry with this software and they need to figure out the condenser and
evaporator saturation temperature in this model.
Chunlu Zhang and his research group introduced a newly developed general
simulation platform, GREATLAB, in the College of Mechanical Engineering at Tongji
University in Shanghai, China (Chunlu, 2012b). Several component models are included
in this platform. The bifurcation diagram is illustrated in Figure 1.2. The CoilLab
concentrates on coil design and optimization. The CompLab focuses on compressor
modeling construction within AHRI 10-coefficient compressor maps, while the FanLab
designs for fan design. GREATLAB combines all the sub-software into its platform to
achieve the vapor compression cycle simulation. Users can define their own vapor
compressor cycle in GREATLAB pro, which is a more expansive version than the
standard one. The major projects for the GreatLAB are RTUs, train air-conditioners, and
electronic cooling.
GREATLAB
CoilLab
CompLab
FanLab
Figure 1-4 GreatLab and its components
OtherLabs
23
FrigoSim is a vapor compression cycle software particularly aimed at refrigeration
plants and heat pump systems. Semi-hardware based models of heat exchangers are
included in the FrigoSim software (Andresen, 2009).
Sarkar et al. (2006) represented a simulation tool focusing on refrigeration cycle,
which is a hardware-based one. This program package can optimize the cycle for
maximum COP and equation sets that can be solved by the Newton-Paphson method
(Sarkar, Bhattacharyya, & Gopal, 2006).
The Heat Pump Design Model (HPDM) is a steady-state design analysis research tool
for heat pumps and air conditioning systems (Rice, 2015). Hiller and Glicksman, at the
Massachusetts Institute of Technology (MIT), developed the original basic models for
compressors and heat exchangers in 1976. In 1978, the first HPDM version was created
by Ellison and Creswick using FORTRAN programs. The Mark I version was generated
by Fischer and Rice in 1983, and the first PC version was released as Mark III in 1985.
Followed by the version Mark IV, the variable-speed model, was achieved with design
parametric capabilities and added electronically commutated motors (ECMs) (Heat et al.,
1997). The latest Heat Pump Design Model version is Mark VII, which was upgraded in
2005 and 2006 within the ASHRAE Technical Research Project (TRP)-1173 (B. Shen,
July 2006). The major projects that the HPDM operating are RTUs. It requires several
heat exchanger geometries, compressor map input parameters, system operation
conditions, and other values. Users can define their own heat exchangers and reasonable
compressor map representations. Simulated by the HPDM, the system capacity, power
consumption, mass flow rate and other key parameters will be displayed. Input and
output will be more fully discussed in Chapter 3 of this thesis.
24
1.3. Motivation and Objectives
There is limited research on mini-split heat pump systems in the U.S., which are
more and more significant on residential buildings. In addition, the models that people
can find are mainly for RTUs. HPDM operated well in split systems within large DOE
projects and provided accurate simulation results. Moreover, rooftop units have similar
refrigeration components to mini-split heat pump systems. Therefore, an investigation of
a generic benchmark for mini-split heat pump system is of interest and needs to be
researched.
The objectives of this thesis are:

Describe the methodology for utilizing the Heat Pump Design Model.

Determine system inputs and outputs.

Determine whether the compressor map scaling method in rotary compressor
maps and scroll compressor maps can be utilized in a mini-split heat pump
system.

Compare and analyze lab and manufactural simulation data results obtained
be the HPDM with lab and manufactural performance data for cooling and
heating modes.

Generate a generic benchmark for a mini-split heat system within a certain
temperature range.
25
1.4. Methodology
The Heat Pump Design Model utilizes a physical model to achieve the stated
objectives. With five different kinds of inputs, the HPDM can generate detailed simulated
data which will be considered to compare with laboratory and manufactural performance
data in both cooling and heating modes. The relative errors for several key outputs, like
system capacity, mass flow rate, power consumption and other parameters, will be
specified in order to investigate whether the HPDM can be a generic benchmark for a
mini-split heat pump system.
1.5. Thesis Organization
The first chapter introduced the background for a mini-split heat pump system and the
importance to generate a generic benchmark for that. Literature reviews about related
models and their functions are provided. In addition, the research motivations and
objectives are touched on and system methodology is discussed in the first chapter.
The second chapter focuses on the data sources. Laboratory data and manufactural
data sets are offered to validate the research method. The third chapter illustrates the
methodology for utilizing the HPDM, illustrates functions for five kinds of inputs and
several key outputs after simulation. Two case studies are discussed in the fourth chapter.
They are lab and manufactural simulation results compared to lab and manufactural
performance data, separately. The final chapter summarizes several main conclusions for
this thesis and suggestions for future studies.
26
CHAPTER 2.
DATA SOURCES
2.1. Overview
There are two types of data sources used for simulations. The first one is the
laboratory data and the second one is the manufactural data both for cooling mode and
heating mode. The laboratory data (Cheung & Braun, 2014) was tested by Dr. Howard
Cheung and Dr. David Yuill in the Herrick Laboratory at Purdue University. The
manufactural data is provided by LG air conditioner engineer product data book. The
testing unit is an LG unit, termed as LA096HV, which is a mini-split heat pump system
with rated cooling capacity being 9000 Btu/hr and rated heating capacity being 11,700
Btu/hr.
2.2. Laboratory Data
The lab data can be divided into two sections which are cooling test performance sets
and heating test performance sets, separately. The lab data sets include several
performance data under the circumstance of the maximum compressor speed.
Furthermore, the lab data sets were obtained at combinations of ambient temperature
( ) of 67, 87, 95, 105 and 115 F, indoor dry-bulb temperature ( ) of 74 and 80 F
and, indoor wet-bulb temperature ( ) of 56, 62, 66 and 67 F in the cooling mode.
Simultaneously, the lab data sets were also gathered as the combinations of indoor drybulb temperature of 64 and 70 F, outdoor dry-bulb temperature of 7,17, 27, 35, 42, 47, 62
27
and 68 F, outdoor wet-bulb temperature of 6, 15, 23, 30, 35, 37, 40, 48, 51 and 53 F in
the heating mode. Using the psychrometric chamber in the Herrick Laboratory at Purdue
University, lab performance data could be obtained. The lab performance data include
indoor coil refrigerant side cooling capacity, system refrigerant charge, the coefficient of
performance (COP), energy efficiency ratio (EER), sensible heat ratio (SHR), refrigerant
mass flow rate, power consumption and other parameters for both cooling tests and
heating tests.
2.3. Manufacturing Data
There are also two components of manufactural data: cooling performance data sets
and heating performance data sets. The manufactural data is also tested within the
maximum compressor speed. The differences between lab data and manufactural data are
the ambient temperature range and the indoor dry-bulb/wet-bulb temperature range. The
range of manufactural data for  , 68 F to 125 F, is larger than that of the laboratory
data and  is either 68, 71.6, 77, 80.6, 86 or 89.6 F. The range of laboratory data for
 is smaller than the manufactural data, identified in Table 2-1 to be 57.2 F to 75.2 F.
In general, manufacturers only provide total capacity, sensible capacity and power
consumption for mini-split heat pump systems. However, SHR can be calculated by
equation (2.1) and power consumption can be computed by equation (2.2). Therefore, the
performance data can be more deeply investigated as total capacity, SHR, and power
consumption.
SHR =
 
 
(2.1)
28
Power consumption =
   +      +
    
(2.2)
To be specific, Table 2-1 shows all performance parameters tested by the
manufacturer with different  ,  , and  in the cooling test mode.
Table 2-1 Manufactural testing data for LG 096HV in the cooling mode
Indoor Air
temperature
DB
WB (F)
(F)
57.2
68
60.8
71.6
64.4
77
66.2
80.6
71.6
75.2
86
89.6
Indoor Air
temperature
0.62
0.57
580
580
68
TC
(Btu/hr)
8837
9383
9929
10202
11021
11567
WB(F)
DB(F)
57.2
68
60.8
71.6
64.4
77
66.2
80.6
71.6
86
75.2
89.6
Indoor Air
temperature
WB(F)
57.2
60.8
64.4
66.2
71.6
75.2
0.85
0.79
0.73
0.71
Outdoor Air Temperature: DB (F)
77
89.6
PI
TC
PI
TC
SHR
SHR
(W)
(Btu/hr)
(W)
(Btu/hr)
390
8462
0.90
410
7916
0.98
530
8974
0.83
540
8462
0.90
570
9519
0.77
580
9008
0.83
580
9792
0.75
590
9281
0.80
DB(F)
68
71.6
77
80.6
86
89.6
SHR
TC(Btu/hr)
7677
8223
8769
9008
9827
10372
PI
(W)
550
650
680
690
10611
0.65
600
10099
0.70
700
11157
0.60
600
10611
0.64
720
Outdoor Air Temperature: DB (F)
95
104
SHR
PI(W)
TC(Btu/hr)
SHR
PI(W)
1.03
610
7370
1.06
670
0.94
700
7882
0.98
730
0.87
720
8428
0.89
740
0.84
710
8701
0.87
740
0.73
740
9485
0.75
750
0.67
760
10031
0.69
770
Outdoor Air Temperature: DB (F)
109.4
TC(Btu/hr)
SHR
7165
1.11
7677
1.02
8223
0.93
8496
0.90
9281
0.78
9827
0.72
PI(W)
660
690
690
690
700
710
114.8
TC(Btu/hr)
SHR
6960
1.15
7472
1.05
8018
0.96
8291
0.93
9076
0.80
9622
0.73
PI(W)
590
600
590
580
580
590
29
For the manufactural performance parameters presented in Table 2-1, TC stands for
the total capacity in a certain outdoor air temperature and indoor dry-bulb/wet-bulb
temperature, while PI is the abbreviation for the total power input which means the same
as total power consumption. The yellow highlighted cells are varied  and The blue
highlighted columns represent  and  . The rated condition whose total cooling
capacity is 9008 Btu/hr is shown in red font in Table 2-1.
Simultaneously, there are also detailed manufactural testing results for the heating
mode within varied outdoor wet-bulb temperature ( ) and indoor dry-bulb
temperature. Table 2-2 shows the results of the heating mode for this unit.
Table 2-2 Manufactural testing data for LG 096HV in the heating model
Indoor Air
Temperature
DB(F)
60.8
64.4
68
69.8
71.6
75.2
Indoor Air
Temperature
DB(F)
60.8
64.4
68
69.8
71.6
75.2
Outdoor Air Temperature: WB (F)
5
TC(Btu/hr)
PI(W)
8803
8701
8665
8632
8632
8396
750
760
770
780
790
810
42.8
TC(Btu/hr)
11908
11806
11703
11635
11533
11464
14
TC(Btu/hr)
PI(W)
23
TC(Btu/hr)
PI(W)
9247
730
10031
770
9247
750
10031
790
9247
770
10065
810
9247
780
10065
820
9247
790
10031
830
9144
810
9929
860
Outdoor Air Temperature: WB (F)
32
TC(Btu/hr)
PI(W)
10714
10714
10680
10645
10645
10543
820
850
870
880
890
910
PI(W)
50
TC(Btu/hr)
PI(W)
59
TC(Btu/hr)
PI(W)
880
900
920
930
940
950
12556
12420
12317
12317
12317
12113
920
930
950
950
960
970
13648
13614
13614
13546
13409
13273
980
990
990
990
990
1000
30
The manufactural parameters for heating mode are listed in Table 2-2. The yellow
highlighted cells are varied  from 5 F to 59 F. In addition, the blue highlighted
columns representation of  . The rated situation whose total heating capacity is 11703
Btu/hr is also marked in red font in this table.
CHAPTER 3.
DOE/ORNL HEAT PUMP DESIGN MODEL
The DOE/ORNL Heat Pump Design Model is a very useful research tool for
simulating refrigeration cycles for heat pump systems and air conditioners system. The
software was developed by Oak Ridge National Laboratory for the U.S. Department of
Energy. It is a no charge program for anyone to do simulations for vapor compression
cycles. In section 3.1, the definition, strengths, the Heat Pump Design Model will be
discussed. Moreover, the basic methodology of Heat Pump Design Models is desired to
be presented in section 3.2.
3.1. Introduction to the Heat Pump Design Model
In this section, Heat Pump Design Model will be defined and a large number of
advantages and a few of disadvantages will also be provided. The Heat Pump Design
Model (HPDM) is a web-based research software platform that analyzes a steady-state
design of air-to-air heat pumps and air conditioners, whose interface is presented in
Figure 3-1 (ORNL, 2015). Additionally, the HPDM can be utilized this software online
31
freely. This program comprises of several strengths which will discuss more in the next
paragraph.
Figure 3-1 The interface for the DOE/ORNL Heat Pump Design Model
In the real world, the HPDM is a useful and effective program that has already been
employed in several great essential projects. One example is Advanced variable speed
air-source integrated heat pump (AS-IHP)(Baxter, 2014). This project is funded by U.S.
Department of Energy with a total budget $2,120,000. Researchers utilized the Heat
Pump Design Model to develop the prototype design and lab prototype test system
proposal. Calibrated by HPDM, researchers developed test results. Another application of
this software is for Cold Climate Heat Pump (CCHP) research projects, also funded by
the Department of Energy. Oak Ridge National Laboratory (ORNL) and Emerson
Climate Technologies worked together for a Cooperative Research and Development
Agreement (CRADA) to investigate a Cold Climate Heat Pump for the residential market
32
in the U.S between 2011 and 2015 (Bouza, 2016). Creating the urgency to develop more
about this, there are lots of states in cold or very cold zones, shown in Figure 3-2. This
figure is obtained from “High-Performance Home Technologies Guide to Determining
Climate Regions by County” at Pacific Northwest National Laboratory (PNNL) and
ORNL in August 2010.
In the CCHP projects, researchers achieve building energy models by utilizing the
HPDM. In theory, the Heat Pump Design Model is a physical model, which means that
models are provided by physical or engineering principles and the most accurate
estimators of output can be obtained when models are operated accurately (Katipamula &
Brambley, 2005). Also, the HPDM has already achieved several rooftop units (RTU)’s
projects for the U.S. DOE. Therefore, the Heat Pump Design Model is an accurate and
reliable software both in reality and theory for RTUs.
Figure 3-2 Climate distributed zones in the U.S.
33
3.2. Methodology of Heat Pump Design Model
In order to utilize the HPDM proficiently, researchers are required to identify exactly
the real methodology for this software application for every input parameter.
Additionally, the Heat Pump Design Model is a physical model so operators need to
specify a large number of details which will be discussed in this section. More specific
parameters which will have to be input will be exposed and analyzed. The Heat Pump
Design Model inputs should be identified as 5 different parameters.

General System Descriptions

System Refrigerant-Side Balancing

Compressor Characteristics

Fin-and-Tube Heat Exchanger Parameters and Configurations

System Operating Conditions
Since the input parameters for the HPDM are not simple values, their meanings and
applications are described in particular in the following five sections.
3.2.1 General System Descriptions
Users need to specify whether they are using air conditioners or heat pump systems.
In addition, the refrigerant for the system is required to be confirmed by operators.
Typically, for the mini split heat pump system, manufacturers would prefer R22 as the
system refrigerant in the past, but now they prefer to apply R410A for system refrigerant,
34
since R410a is more environmentally friendly, not contributing to ozone depletion, and
absorbing and releasing more heat than R22 (Thien, 2012). Figure 3-3 shows the
interface of general system descriptions when users are specifying the system and the
refrigerant. Users select cooling mode or heating mode and the refrigerant they are
utilizing.
Figure 3-3 The interface of General System Description
3.2.2 System Refrigerant-Side Balancing
The next item users need to indicate is the system refrigerant-side balancing. There
are three important parameters that users need to recognize: system refrigerant charge,
superheat temperature and subcooling temperature. If a user specifies any two of these
three parameters and estimates the third, they can achieve the system refrigerant-side
balancing target. As shown in Figure 3-4, there are three combination arrangements for
35
these three parameters. SH means the compressor inlet superheat temperature, while SC
means the condenser exit subcooling temperature or flow control devices. If the user has
the ability to identify the flow control equipment details, like capillary tubes, short-tube
orifices or thermostatic expansion valves, the SC input can be satisfied. Otherwise, users
need to specify the condenser exit subcooling temperature. Mass is the abbreviation of
the system refrigerant charge. Therefore, as long as individuals specify any two of these
three parameters and guess estimate the third, the system will make the iteration
computations.
Figure 3-4 Three different ways to achieve system refrigerant-side balancing
For the purpose of investigating how the system operates, the three methodologies
will be explored using three logic diagrams in the next succeeding pages. With great
contributions to the Heat Pump Design Model by the research group, these three logical
schemes were obtained and are represented here.
36
SH, calc
Figure 3-5 the logic diagram for specifying SH and SC
37
Figure 3-6 the logic diagram for specifying SC and system refrigerant charge
38
Figure 3-7 the logic diagram for specifying SH and system refrigerant charge
39
The Figures 3-5, 3-6, and 3-7 are different logic diagrams in three various specified
conditions. Shown in Figure 3-5, if users have already discerned the superheat
temperature and subcooling temperature for the operation system, they input these two
parameters into the Heat Pump Design Model. After several steps’ computations, the
HPDM will calculate the subcooling temperature by itself. Comparing calculated
subcooling temperature and specified subcooling temperature, if the absolute difference
value of these two parameters is smaller than the setting value, whose default value is 0.2
F, the HPDM will continue computations to evaporator superheat temperature
calculations. Otherwise, the HPDM will need to change the condenser side pressure to
satisfy the requirement of the previous conditional statement. As the similar condition, if
the absolute difference value between calculated superheat temperature and the specified
superheat temperature is less than the setting value, whose default value is 0.5 F, the
HPDM will compare the calculated indoor dry-bulb temperature with the  , which is
specified in the operation condition. Moreover, the default absolute difference of indoor
dry-bulb temperature is 0.1 F, which means that the calculation result should be less than
the setting value. If the superheat temperature calculation result does not satisfy the
setting condition, the Heat Pump Design Model will change  to allow system
convergence. If the  does not match with the setting value, the HPDM will change the
evaporator side pressure in order to get a good result. The first logic diagram will print
the results by filling the content with all of the conditional statements mentioned above.
The second and the third conditions operate on the same principle but change with
specified superheat temperature or subcooling temperature. For example, for the second
condition, Figure 3-6, users need to identify subcooling temperature or flow control
40
device and the amount of refrigerant mass. In addition, it is necessary to estimate
superheat temperature in order to achieve the operation objective. After a basic cycle
balance calculation, the HPDM will calculate the system refrigerant charge. If the
calculated one is close enough to the specified one, the system loop will be terminated.
Otherwise, the Heat Pump Design Model will need to change the estimated superheat
temperature to satisfy the conditional statement. The third situation shares the same
principle with the second condition, which is explained in Figure 3-7.
3.2.3 Compressor characteristics
The compressor is the most important part of the whole refrigeration system and the
importance could be compared to the heart of a man. Therefore, there is an indispensable
need for researchers to investigate more about compressor characteristics. In this section,
there are three pieces of information that need to be known: compressor selection,
compressor data, and compressor calibration, as shown in Figure 3-8.
Compressor
characteristics
Compressor
selection
Compressor
data
Compressor
calibration
Figure 3-8 The components of compressor characteristics
41
3.2.3.1 Compressor selections
Users can select preconfigured compressors or input their own compressor
characteristics. Figure 3-9 shows the interface for compressor selection that people could
specify their own compressors or just select default ones.
Figure 3-9 the interface for compressor selection
3.2.3.2 Compressor data
After selecting the compressor, users need to specify some detailed compressor data,
represented in Figure 3-10. These details are rated EER, rated cooling capacity, rated
inlet condition (superheat/return gas temperature) and compressor map equations.
Moreover, if users recognize the total displacement, motor size, nominal speed and
nominal voltage, they can also input these optional parameters. Otherwise, the HPDM
will generate them itself.
42
Figure 3-10 the interface of compressor data
A compressor map is an essential part of the compressor data. Based on the
compressor map, the Heat Pump Design Model can generate the results of compressor
power consumption and compressor mass flow rate. Equation 3.1 represents the system
compressor map.
( ,  ) = 1 + 2  + 3  + 4 2 + 5   + 6 2 + 7 3 + 8  2 + 9  2 + 10 3
where
1 − 10 are the coefficients found by the linear regression method.
 and  are the compressor suction and discharge saturation temperature,
respectively.
(3.1)
43
Typically, the rated compressor parameters can be found in the manufacturer
brochures. However, the compressor map cannot be obtained very easily for some large
companies. If a user cannot specify the compressor map for the refrigeration system, the
system loop cannot be simulated, therefore, there is no doubt that users need to find a
method which can generate a compressor map that is very similar to the manufacturers.
In industry, companies would like to scale compressor maps in order to get a new
compressor map which is standard for those manufacturers. Thus, a scaling method to
achieve this goal is introduced here.
Scaling method:
Adjustment Factor(AF) =
_    ×
  
  
  
_   ×
  
= _   
  
  
= _  
(3.2)
(3.3)
(3.4)
Where
_    is the mass flow rate of the based compressor map.
_    is the mass flow rate of the predicted compressor map.
_   is the compressor power consumption of the based one.
_   is the compressor power consumption of the predicted one.
For this scaling method, the Adjustment Factor (AF) should be explained first. A
baseline compressor map could be found with no trouble since there are large amounts of
44
compressor maps provided by U.S. companies. In addition, the predicted rated cooling
capacity and the base rated cooling capacity could be recognized conveniently from the
manufactural data. Therefore, the AF can be computed from Equation 3.2.
The second step is to get every point of mass flow rate and power consumption
within the different evaporating temperature and condensing temperature. According to
Equations 3.3 and 3.4, the predicted mass flow rate and the predicted power consumption
is not complicated to calculate. Here are some examples to illustrate this claim.
Typically, for the mini-split heat pump system, manufacturers would like to prefer
the rotary compressor or scroll compressor since their operation range is more suitable
for residential applications. From Figure 3-11, the cooling capacities of rotary
compressors are around 1 ton, while the cooling capacities of scroll compressors are from
1 to 10 tons (Mitchell & Braun, 2011). Therefore, the examples focus more on scaling the
rotary compressors and scroll compressors.
Figure 3-11 Ranges of capacity applications for different compressor types
45
Three compressor maps from the TECUMECH company are used for the rotary
compressors. The rated cooling capacities are 5300 Btu/hr, 7125 Btu/hr and 10150
Btu/hr, respectively. Important to note is that all three of these compressors have the
same voltage, frequency, refrigerant, phase, and application. Setting the rated cooling
capacity of 7125 Btu/hr as the base rated cooling capacity, the rated cooling capacity of
5300 Btu/hr and 10150 Btu/ hr can be set as predicted rated cooling capacities.
Meanwhile, according to Equation 3.1, the Adjustment Factor could be computed without
any difficulties.
Figure 3-12 the AF for the rotary compressors examples
When utilizing the cooling capacity of the 7125 Btu/hr compressor map to predict the
cooling capacity of the 11740 Btu/hr compressor map, the Adjustment factor is 1.648.
The relative error calculation is shown in Equation 3.5.
Relative error =
(Predicted parameters−Based parameters)
Based parameters
(3.5)
46
For example, researchers can predict the mass flow rate and power consumption as
the procedures as below.
Based on Appendix I, the rated cooling capacity of the compressor map for 7125
Btu/hr, the mass flow rate is 93.2 lb/hr and power consumption is 660 w, when the
condensing temperature is 40 F and evaporating temperature is 120 F. Based on
Appendix II, the rated cooling capacity of the compressor map for 11740 Btu/hr, the mass
flow rate is 156 lb/hr and power consumption is 1110 w, when the condensing
temperature is 40 F and evaporating temperature is 120 F.
Predicted mass flow rate
= Based mass flow rate * AF
= 93.2 lbm/hr ∗ 1.648
= 153.6 lbm/hr
Predicted power consumption
= Based power consumption * AF
= 660 w ∗ 1.648
= 1087.7 w
After obtaining the predicted mass flow rate and power consumption at the specified
point, researchers can compute the relative errors for these two parameters.
47
Relative error of the mass flow rate
=
=
(   −   )
   
153.6 lbm/hr−156 /ℎ
156 /ℎ
= -1.56%
Relative error of power consumption
=
=
(   −  )
  
1087.7 w−1110 
1110 
= -2.03%
The example point is marked as red in Table 3-1 and Table 3-2. Moreover, this is an
example of a specified point, but researchers need to generate all points in every
condensing temperature and evaporating temperature. Microsoft Excel can be the
utilization tool to achieve these. After computing relative errors for mass flow rates and
power consumptions, the prediction from rated cooling capacity 7125 Btu/hr to rated
cooling capacity 11740 Btu/hr, relative errors can be calculated. The relative errors of
power consumptions and mass flow rates are shown in Tables 3-1 and 3-2.
From these two tables, researchers can easily deduct that the maximum relative error
for power consumption is - 4.73%, which is marked as blue in Table 3-1, when the
48
condensing temperature is -15 F and the evaporating temperature is 80 F. The average of
relative errors for every condition is -2.67% and the standard deviation is determined to
be 0.80% after computing in Excel. Simultaneously, the maximum relative error for mass
flow rate is -5.75% which can be observed in a blue font in Table 3-2, when the
condensing temperature is -15 F and evaporating temperature is 80 F. The average of
relative errors for every situation is -1.39% and the standard deviation is 0.99%.
Table 3-1 Relative errors for power consumption prediction from 7125 Btu/hr to 11740 Btu/hr
Relative Error
Tcond(F)
Tevap(F)
80
Power consumption prediction
100
110
120
130
90
-15
-4.73%
-4.72%
-10
-4.19%
-3.76%
-3.49%
-5
-3.50%
-3.23%
-2.90%
-2.61%
0
-3.25%
-2.89%
-2.70%
-2.34%
-2.03%
5
-3.14%
-2.82%
-2.44%
-2.03%
-1.77%
10
15
20
25
30
35
40
45
50
55
-3.09%
-3.09%
-3.23%
-3.43%
-3.65%
-3.81%
-3.74%
-4.09%
-3.97%
-3.86%
-2.68%
-2.59%
-2.74%
-3.03%
-3.04%
-3.27%
-3.34%
-3.65%
-3.55%
-3.46%
-2.34%
-2.36%
-2.53%
-2.52%
-2.73%
-2.78%
-3.04%
-3.03%
-3.25%
-3.19%
-2.04%
-1.92%
-2.18%
-2.20%
-2.13%
-2.93%
-3.09%
-2.62%
-2.93%
-2.99%
-2.11%
-1.61%
-1.45%
-1.75%
-2.34%
-2.47%
-2.03%
-2.76%
-3.05%
-2.77%
-1.89%
-1.73%
-1.14%
-1.70%
-1.69%
-2.09%
-1.95%
-2.07%
-2.60%
-2.73%
140
-0.71%
-0.86%
-1.40%
-1.53%
-1.78%
-1.64%
-1.76%
-2.24%
-2.23%
-2.58%
49
Table 3-2 Relative errors for mass flow rate prediction from 7125 Btu/hr to 10150 Btu/hr
Relative Error Tevap(F)
Tcond(F)
80
-15
-5.75%
-10
-4.18%
-5
-3.00%
0
-2.28%
5
-1.91%
10
-1.60%
15
-1.62%
20
-1.28%
25
-1.01%
30
-0.90%
35
-0.72%
40
-0.95%
45
-0.27%
50
0.30%
55
-0.12%
90
-4.82%
-3.38%
-2.48%
-1.99%
-1.60%
-1.47%
-1.27%
-1.43%
-1.53%
-0.78%
-0.92%
-0.55%
-0.25%
-0.97%
-0.09%
Mass flow rate prediction
100
110
120
-2.65%
-1.91%
-1.43%
-1.27%
-1.21%
-1.17%
-0.83%
-1.14%
-1.50%
-1.14%
-1.44%
-0.77%
-0.97%
-0.83%
-0.96%
-0.78%
-0.87%
-0.82%
-0.96%
-1.14%
-1.70%
-1.51%
-1.25%
-1.14%
-1.32%
-1.48%
-1.29%
-0.02%
-0.15%
-0.48%
-0.81%
-1.46%
-1.43%
-1.53%
-1.49%
-1.56%
-1.33%
-1.49%
-2.09%
130
140
0.16%
-0.41%
-0.87%
-1.29%
-1.54%
-1.86%
-2.11%
-1.73%
-2.39%
-2.12%
0.76%
0.13%
-0.54%
-0.98%
-1.55%
-2.13%
-1.92%
-2.35%
-2.43%
-2.48%
Most of the time, the manufacturer will use rotary compressors for mini-split heat
pump systems in residential applications. Therefore, one more example of compressor
map prediction is provided as follows.
With the same principles, utilizing rated cooling capacity of the 7125 Btu/hr
compressor map to predict rated cooling capacity for the 5300 Btu/hr compressor map,
the results for relative errors are shown in Tables 3-3 and 3-4. The Adjustment Factor of
this prediction is 0.744.
50
Table 3-3 Relative errors for power consumption prediction from 7125 Btu/hr to 5300 Btu/hr
Relative Error Tevap(F)
Tcond(F)
80
-15
-2.35%
-10
-2.54%
-5
-2.05%
0
-1.96%
5
-1.95%
10
-2.09%
15
-1.79%
20
-1.87%
25
-1.81%
30
-2.14%
35
-2.01%
40
-2.05%
45
-2.43%
50
-2.42%
55
-2.88%
90
-2.73%
-2.37%
-2.40%
-2.01%
-1.99%
-1.84%
-1.83%
-1.63%
-1.77%
-1.57%
-1.65%
-1.67%
-1.98%
-1.94%
-1.98%
Power consumption prediction
100
110
120
130
-2.49%
-2.23%
-2.06%
-2.03%
-1.89%
-1.81%
-1.62%
-1.55%
-1.55%
-1.43%
-1.38%
-1.45%
-1.59%
-1.61%
-2.33%
-2.16%
-1.89%
-1.92%
-1.67%
-1.66%
-1.38%
-1.37%
-1.21%
-1.15%
-1.21%
-1.32%
-1.33%
-2.25%
-1.98%
-1.79%
-1.51%
-1.34%
-1.23%
-1.22%
-1.07%
-1.02%
-0.87%
-0.97%
-0.77%
-1.68%
-1.41%
-1.40%
-1.29%
-1.10%
-0.96%
-0.91%
-0.77%
-0.68%
-0.64%
140
-1.62%
-1.37%
-1.18%
-1.21%
-0.86%
-0.73%
-0.69%
-0.53%
-0.45%
-0.57%
Table 3-4 Relative errors for mass flow rate prediction from 7125 Btu/hr to 5300 Btu/hr
Relative Error Tevap(F)
Tcond(F)
80
-15
-3.74%
-10
-2.79%
-5
-2.12%
0
-1.66%
5
-1.63%
10
-1.19%
15
-1.24%
20
-0.87%
25
-0.69%
30
-0.59%
35
-0.47%
40
-0.56%
45
0.17%
50
0.35%
55
-0.09%
90
-1.17%
-0.71%
-0.82%
-0.66%
-0.68%
-0.26%
-0.51%
-0.32%
-0.42%
-0.30%
-0.24%
0.36%
0.26%
-0.27%
0.38%
Mass flow rate prediction
100
110
120
1.26%
0.99%
1.02%
0.65%
0.33%
0.55%
0.11%
0.19%
0.05%
0.00%
-0.11%
0.35%
-0.09%
-0.10%
3.00%
2.61%
1.88%
1.22%
1.69%
0.78%
0.71%
0.42%
0.37%
0.30%
0.44%
0.22%
0.29%
4.08%
3.56%
2.00%
2.73%
1.74%
1.26%
0.82%
0.65%
0.47%
0.68%
0.55%
-0.11%
130
140
3.12%
4.19%
2.37%
1.91%
1.44%
1.00%
0.71%
0.53%
-0.02%
0.30%
4.64%
5.89%
3.56%
2.78%
2.10%
1.49%
1.07%
0.78%
0.32%
-0.01%
51
Based on these two tables listed above, the maximum relative error for power
consumption is -2.88% which is marked as blue in Table 3-1, when the condensing
temperature is 55 F and evaporating temperature is 80 F. The average of relative errors
for every condition is -1.61% and the standard deviation is 0.54%. Meanwhile, the
maximum relative error for mass flow rate is 5.89% which can be seen in a blue font in
Table 3-2, when the condensing temperature is 15 F and evaporating temperature is 140
F. The average of relative errors for every situation is 0.60% and the standard deviation is
1.55%.
From these two examples analyzed above, the maximum relative error for mass flow
rate prediction and power consumption prediction is around 5% and average relative error
is below 5%. Thus, the compressor map prediction method is convincing for rotary
compressors.
For the scroll compressors, two compressor maps from the TECUMECH company
are provided afterward. The rated cooling capacities are 28,999 Btu/hr and 56,898 Btu/hr,
respectively. In addition, the Adjustment Factor is 1.962, presented in Figure 3-13.
Figure 3-13 The AF for the scroll compressors example
52
Scroll compressors are also widely utilized in residential applications and the rated
cooling capacity is around 1 to 10 tons, based on Figure 3-11. In order to test scaling
method feasibility for scroll compressors, one example would like to be provided as
follows.
In this example, a compressor map of the rated cooling capacity for 28,999 Btu/hr is
used to predict a compressor map of the rated cooling capacity for 56,898 Btu/hr. Also,
mass flow rate and power consumption are the parameters that need to be predicted. The
scaling principles are the same as the rotary compressors prediction.
Table 3-5 Relative errors for power consumption prediction from 28999 Btu/hr to 56898 Btu/hr
Relative Error
Tcond(F)
-15
-10
-5
0
5
10
15
20
25
30
35
40
45
50
55
Tevap(F)
80
1.93%
2.20%
2.80%
2.48%
2.18%
2.20%
2.56%
2.62%
2.37%
2.46%
2.55%
2.67%
2.43%
1.82%
2.34%
90
2.50%
2.14%
2.39%
2.37%
2.37%
2.37%
2.39%
2.72%
2.47%
2.52%
2.29%
2.37%
2.45%
2.53%
1.98%
Power consumption prediction
100
110
120
130
3.05%
3.00%
2.70%
2.94%
2.94%
2.70%
2.46%
2.75%
2.53%
2.57%
2.62%
2.42%
2.75%
2.54%
2.67%
3.10%
3.08%
3.08%
2.62%
3.10%
3.12%
2.93%
2.73%
2.77%
2.82%
2.87%
2.91%
3.50%
3.08%
3.08%
3.29%
3.31%
3.33%
3.16%
2.99%
3.03%
3.07%
3.11%
3.16%
3.34%
3.36%
3.38%
3.58%
3.44%
3.47%
3.51%
3.38%
3.42%
3.66%
140
3.59%
3.77%
3.80%
3.53%
3.73%
3.61%
3.82%
3.70%
3.76%
3.64%
53
Table 3-6 Relative errors for mass flow rate prediction from 28999 Btu/hr to 56898 Btu/hr
Relative Error
Tcond(F)
-15
-10
-5
0
5
10
15
20
25
30
35
40
45
50
55
Tevap(F)
80
-0.11%
-0.05%
0.00%
-0.24%
-0.43%
-0.37%
-0.13%
-0.31%
-0.29%
-0.44%
-0.31%
-0.45%
-0.24%
-0.38%
0.14%
90
0.09%
0.11%
0.12%
0.13%
-0.38%
-0.33%
-0.09%
-0.09%
-0.27%
-0.12%
-0.42%
-0.31%
-0.34%
-0.27%
0.16%
100
Mass flow rate prediction
110
120
130
-0.60%
-0.47%
-0.39%
-0.32%
-0.51%
-0.46%
-0.06%
-0.08%
-0.10%
-0.13%
-0.29%
-0.21%
-0.36%
-0.59%
0.01%
0.01%
0.02%
0.01%
-0.21%
-0.21%
-0.05%
-0.07%
-0.25%
-0.15%
-0.08%
-0.24%
-0.39%
0.16%
0.13%
-0.40%
0.07%
-0.16%
-0.17%
-0.03%
-0.08%
0.01%
0.06%
-0.11%
-0.56%
-0.30%
0.18%
0.13%
-0.10%
-0.13%
0.12%
0.06%
-0.01%
0.14%
-0.54%
140
0.18%
0.12%
0.28%
0.21%
0.31%
0.07%
0.14%
0.06%
0.10%
0.11%
After calculated by Excel, the relative errors for the power consumption prediction
and mass flow rate prediction are listed in Tables 3-5 and 3-6. All of the absolute value
results are below 5%. The average relative error for power consumption is 2.89% and the
maximum is 3.82%, which is marked as a blue font when the condensing temperature is
40 F and evaporating temperature is 140 F. Additionally, Standard deviation is an
important method to quantify the amount of variation (Bland & Altman, 1996). The
lower the standard deviation is; the more data points are close to the mean value
(WIKIPEDIA, 2016b). Otherwise, the higher the standard deviation is; the fewer data
points are close to the average value. The standard deviation of relative errors for power
consumption is 0.49%, which is very small. For another, the mean value of relative error
for mass flow rate is -0.13%. The absolute value for a maximum of relative error for mass
54
flow rate prediction is 0.6% and the standard deviation is 0.22%, which is also very
small. Based on these values mentioned above, a conclusion can be obtained by
researchers that the scaling method is also suitable for scroll compressor performance
prediction, since the average value and maximum value for the relative error are both
lower than 5% and the standard deviations are relatively small.
In this section, rotary compressor map prediction and scroll compressor map
prediction for mass flow rate and power consumption were explored. Based on
performance values, the relative error for these two parameters is relatively small.
Therefore, the scaling method for these two compressor maps is reasonable. In addition,
these two kinds of compressors are widely utilized for the mini-split heat pump system.
Therefore, this method can be used in the mini-split heat pump system’s compressor map
prediction.
3.2.3.3 Compressor calibration
There are two functions for compressor calibration: scaling compressor performance
and scaling system performance. When users want to scale the compressor performance,
they can change the value for EER, capacity, and voltage by inputting the exact value or
by inputting a multiplier. For the scaling system performance part, researchers can scale
the system performance by inputting a scaling system capacity within a specific range.
Figures 3-14 and 3-15 show the interfaces for scaling compressor performance and
scaling system performance, respectively. Typically, users will not utilize the compressor
and system performance scaling since the Heat Pump Design Model will get a result by
simulation. However, non-convergence will happen in the HPDM simulation and it will
55
show a system server error on the computer. In this time, users will need to scale the
system capacity within a certain range.
Figure 3-14 the interface for scaling compressor performance
Figure 3-15 the interfaces for scaling system performance
56
3.2.4 Fin-and-Tube Heat Exchanger Parameters and Configurations
In this section, heat exchanger parameters and configurations will be discussed
specifically for indoor units and outdoor units. Figures 3-16 and 3-17 are the interfaces
for the indoor unit configurations and outdoor unit geometries, separately. In addition, the
Heat Pump Design Model requires the same heat exchanger configurations for both
indoor units and outdoor units in cooling mode and heating mode. Fortunately, almost all
of the configurations parameters can be found on the manufacturer brochures. If
researchers can possess the units or units can be donated from manufacturers to
researchers, the configurations parameters can be measured by researchers without
difficulties.
Figure 3-16 the interface of indoor unit heat exchanger configuration
57
Figure 3-17 the interface of outdoor unit heat exchanger configuration
There are several heat exchanger configuration parameters that should be specified.

Tube parameters

Fin parameters

Tube spacing and rows
First, for tube parameters, tube type (smooth or rifled) and material (copper or
aluminum) need to be determined. Moreover, the outer diameter and the wall thickness of
the tube should be input into the Heat Pump Design Model.
Second, in order to achieve the fin parameters, the material and type should also be
determined by users. The material may also be either copper or aluminum. Furthermore,
58
the fin pitch and thickness need to be discerned. Fin pitch is the spacing between the
adjacent fins (Shawn, 2016) and the fin thickness is the thickness of a single fin. In order
to explain unambiguously, the tube outer diameter, the wall thickness of a tube, fin pitch
and fin thickness are presented in Figure 3-18.
Figure 3-18 the geometry diagram of a tube
Finally, for the tube spacing and rows, there are also some geometry parameters
needed to be specified, which include finned face area of a coil, tube spacing in longitude
and transversal, the number of rows, the number of tubes in each row and the number of
equivalent, parallel circuits for two-phase and liquid phase.
For the Heat Pump Design Model, the following parameters are able to be
explained clearly. “P” is the finned face area of a coil. “a” is the longitudinal center-tocenter distance between tubes and “b” is the transverse center-to-center distance between
tubes. “h” is the height for the heat exchanger, and “d” is the depth for this heat
59
exchanger. “#r” is the number of tubes in each row and “#n” is the number of rows.
These are shown in Figure 3-19.
Figure 3-19 a transverse figure for a heat exchanger
60
Figure 3-20 a 3D figure for a heat exchanger
The Figure 3-19 is a schematic diagram of a transverse figure for a heat exchanger.
According to this figure, researchers can discern most of the parameters in this section.
The finned face area of a coil, “P”, can be defined as the product of the length of the heat
exchanger and the width of the heat exchanger, which can be defined as the equation 3.6.
Other detailed parameters can be found in Figures 3-19 and 3-20 easily, except for the
number of equivalent, parallel circuits for two-phase and liquid phase.
61
P =d∗h
(3.6)
The Figure 3-20 is a 3D figure for a heat exchanger and it can be understood much
deeper than the Figure 3-19. This figure shows some basic geometry parameters (Fischer
& Rice, 1983) obtained by the Oak Ridge National Laboratory.
In the last part of this section, the terms “two-phase” and “liquid” regions of the
number of equivalent and parallel circuits for indoor units and outdoor units are
explained. The Heat Pump Design Model divides the heat exchanger into two sections:
two-phase region and liquid region. For an evaporator, the type of equivalent and parallel
circuits can be separated as a two-phase region and superheat region, which is shown in
Figure 3-21. For a condenser, the type of equivalent and parallel circuits can be separated
as a two-phase region and subcooling region (Hahn, 1992), which is presented in Figure
3-22. These two figures are sketches for a typical heat exchanger, and researchers can
understand this parameter more deeply.
Figure 3-21 the diagram for number of equivalent, parallel circuits for an evaporator
62
Figure 3-22 the diagram for number of equivalent, parallel circuits for an evaporator
3.2.5 System Operating Conditions
In this part, the Heat Pump Design Model asks the users the specify several key
parameters which are listed below.

Indoor and outdoor dry-bulb and wet-bulb temperature

Indoor and outdoor air flow rate

Indoor and outdoor blower power consumptions

Static pressure

Vapor lines and liquid lines outer diameters
For these five kinds of parameters, users can input any values into the HPDM to get
results. In addition, whether manufacturers or lab testers, the first four parameters will be
provided. But the last parameter can be discerned from the manufacturer brochures
without difficulties.
63
3.2.6 Simulation results
After inputting all of the parameters, the Heat Pump Design Model will perform the
simulation and output every key point performance result for users. Moreover, system
performance values will also be provided by the HPDM. The system capacity, power
consumption, mass flow rate, sensible heat ratio and system EER or COP are included in
the output results. Typically, there are some key points for a refrigeration cycle, which
are presented as Point 1 through 7 in Figure 3-23. Point 1 and Point 2 represent the inlet
and outlet conditions for a compressor. Additionally, Point 3 and Point 4 show the inlet
and outlet situations for a condenser. Simultaneously, point 5 presents the inlet condition
for an expansion valve. Finally, point 6 and point 7 indicate the inlet and outlet
circumstances for an evaporator. These seven key points are significant for evaluating a
vapor compression cycle. Therefore, the Heat Pump Design Model will generate
performance values for every key point, with respect to pressure, dry-bulb temperature,
saturation temperature, and enthalpy. For Points 1, 2 and 4, the superheat temperature
will be provided in the results interface. For points 5 and 6, the subcooling temperature is
shown in the printed results interface, too.
64
Figure 3-23 Key points for a vapor compression cycle in a P-h diagram
Source:(website owner, 2016)
Moreover, the component sizing and system charge will also be provided in the
results interface. The system charge for the simulation results should be equal or similar
to the provided laboratory data or manufactural data, and system charge comparison can
be a good evaluation method for simulation results. Sometimes, researchers cannot find
all of the geometry data, so they need to estimate some values for configuration data
based on similarly rated cooling capacity heat pump systems. If the relative error of the
system charge is less than 5%, then the estimated values are within a reasonable range.
Component sizing was not considered in this thesis, but there is still a large potential to
utilize it in other research objectives.
The printed results are shown in Figures 3-24 and 3-25, which include system
operating conditions, component sizing, charge and performance data. The system
operating condition and the performance data are in the middle of Figure 3-24. There are
seven large numbers in Figure 3-24, corresponding to the seven numbers in Figure 3-23.
65
Since the Heat Pump Design Model lists the seven key point performance data in the
printed results, researchers can know exactly the refrigeration cycle performance
simulation conditions. The component sizing and system charge are listed in Figure 3-25,
but this project only focused on the system charge in both cooling mode and heating
mode.
66
Figure 3-24 Printed results for system operating conditions and performance
67
Figure 3-25 Printed results for component sizing and system charge
68
After specifying all the input parameters, the Heat Pump Design Model will do the
calculation to generate the outputs. A simple schematic diagram is shown in Figure 3-26
which summarizes all of the input values and output parameters that users should
identify. Therefore, users can understand the HPDM’s computation logic easily enough.
Figure 3-26 Detailed inputs and outputs for the HPDM
In this section, input parameters and output performance values are discussed. In
order to operate the Heat Pump Design Model proficiently, explanations of every input
value are provided and output interpretations are offered. In addition, the logic flow for
utilizing the HPDM is also provided in this chapter, thus, users can understand the
processing methodology of the HPDM conveniently.
69
CHAPTER 4.
A GENERIC BENCHMARK FOR MINI-SPLIT
HEAT PUMP SYSTEM
4.1. Overview
In this chapter two case studies which include laboratory data and manufactural data
simulation for both cooling mode and heating mode are described. The five different
kinds of lab data input parameters for the LG LA096HV will be discussed in section 4.2
and the manufactural data inputs are presented in section 4.3. The simulation results are
described in section 4.4 and detail tables are represented in the appendix. Finally, the
discussions about those simulation results for lab data and manufactural data in both
cooling mode and heating mode are investigated in section 4.5.
4.2. Case study 1: HPDM inputs for the lab data
In the last chapter, the methodology of the Heat Pump Design Model has been
illustrated clearly. Therefore, in this section, several lab data inputs will be examined to
validate the HPDM’s feasibility or effectiveness within a certain temperature range. The
simulated testing unit the author simulating is the LG 096HV, which is a mini-split heat
pump system with a rated cooling capacity of 9000 Btu/hr and rated heating capacity
11,700 Btu/hr.
Since there are total five kinds of the input values, researchers need to determine
each one by one. The first input value should be “General system description”. It is very
70
easy to decide the first input for this unit. Cooling mode and heating mode are both
applied in this LG unit and the refrigerant is the R410A. Therefore, the required first
input can be figured out without any difficulties. Other four kinds of inputs are also
required to be identified. However, the lab data includes the system refrigerant balancing
data (the second input) which consists of superheat temperature, subcooling temperature
and system refrigerant charge. In addition, system operating condition parameters (the
fifth input) are also included in the laboratory data. The compressor characteristics (the
third input) and the detailed geometry configuration values (the fourth input) can be
found online by asking the specified manufacturers or using the methodology provided in
Chapter 3 of this thesis.
The five kinds of detailed inputs for this LG unit will be displayed in the following
paragraphs.
General system description:

Both in cooling mode and heating mode

Refrigerant R410A
System refrigerant side balancing:

System refrigerant charge: 2.3 lbs

Superheat temperature and subcooling temperature will be shown combined with
system operation conditions
The system refrigerant side balancing inputs combined with system operating
condition inputs are list one table for clarity.
71
System operating condition:
As discussed in Chapter 3, the contents of system operating conditions can be found
without difficulties. Therefore, the detailed values for the inputs of system refrigerant
side balancing and the inputs of system operating conditions will be presented in
Appendix VII for the cooling mode, while these two inputs will be presented in Appendix
X for the heating mode.
The static pressure is zero in this testing procedure. Also, the outer diameter of the
liquid line is 1/4 in and the vapor line is 3/8 in for this LG unit. In the next section, the
inputs for compressor characteristics are provided, which is the most important part to
influence system performance.
Compressor characteristics:
This compressor’s rated cooling capacity is 9163 Btu/hr and the rated EER for the
compressor is 9.2. In addition, the rated return gas temperature is 65 F. Most important
for the compressor performance simulation is the compressor map. Unfortunately, the
manufacturer does not provide the compressor map for users, therefore, the scaling
compressor map method should be implemented in order to obtain this specific
compressor map. By utilizing the compressor map of rated cooling capacity 11,740
Btu/hr to predict the compressor map of rated cooling capacity 9173 Btu/hr, the
Adjustment Factor should be specified.
Adjustment Factor(AF) =
  
  
9173 /ℎ
= 11740 /ℎ = 0.7813
72
Multiplying by the AF, the compressor map can be specified reasonable and logical.
Appendix IV shows the compressor map for this compressor. In order to generate the
compressor map equations, the software Easy Equation Solver (EES) will be utilized.
EES has a linear regression function for inputting the data values. Since the
compressor map representations are two 10-coefficient equations for mass flow rate and
power consumption, EES can find the equations immediately and accurately. Tables 4-1
and 4-2 list the coefficients of representations for the compressor map.
Table 4-1 Power consumption coefficients
Power consumption coefficients
C1
245.93753
C2
-6.48637635
C3
3.84440165
C4
-0.061561913
C5
0.098089265
C6
0.003499407
C7
-0.000205588
C8
0.000173891
C9
-1.77976E-05
C10
-6.06368E-06
Table 4-2 Mass flow rate coefficients
Mass flow rate coefficients
C1
87.6772433
C2
1.63236463
C3
-0.668987207
C4
0.015336757
C5
-0.003167124
C6
0.004620506
C7
-1.82561E-05
C8
4.90809E-06
C9
-1.13937E-06
C10
-1.48437E-05
73
Figure 4-1 The diagram power consumption linear regression
Figure 4-2 The diagram for mass flow rate linear regression
74
Figures 4-1 and 4-2 illustrate the degree of fit for compressor maps for mass flow
rate and power consumption equations, utilizing the linear regression method in EES.
Based on these two figures, the prediction compressor maps demonstrate a good fit, since
all of the points are on the linear fit lines for both the compressor maps for mass flow rate
and power consumption. To determine the compressor map to input, some optional
parameters might be ascertained, illustrated in the following paragraph.
There are four optional parameters used to determine the Heat Pump Design Model
–compressor displacement, compressor motor size, the nominal speed and the nominal
voltage for the compressor. For this LG unit, the compressor displacement is 0.8 in3 /rev
and the compressor motor size is 0.88 hp. In addition, the nominal speed and the nominal
voltage for this compressor are 3500 rpm and 230 v, respectively.
Fin and tube heat exchanger parameters and configurations:
The most difficult information to determine is the heat exchanger geometry
parameters, since manufacturers do not generally provide all of these parameters.
However, if researchers can find them online or by asking professional workers, they can
specify those parameters accurately. For this LG unit, thanks to Dr. Howard Cheung,
most of the geometry configurations are provided by his measurement.
75
Table 4-3 heat exchanger parameters for the indoor unit
Fin
Indoor unit
Tube
Material
Type
OD
Wall
Frontal area
Tube spacing (a)
Tube spacing (b)
Cu
smooth
0.289
in
30
mils
2.217
ft2
0.827
in
0.489
in
Material
Al
Type
smooth
Pitch
20
fins/in
Thickness
6.05
mils
Number of rows
2
Number of tubes/row(n)
15
Number of equivalent, parallel circuits
two-phase
1
liquid phase
1
Table 4-4 heat exchanger parameters for the outdoor unit
Fin
Outdoor unit
Tube
Material
Type
OD
Wall
Frontal area
Tube spacing (a)
Tube spacing (b)
Cu
smooth
0.282
in
30
mils
4.83
ft2
0.798
in
0.72
in
Material
Al
Type
smooth
Pitch
17 fins/in
Thickness
6.89
mils
Number of rows
2
Number of tubes/row(n)
24
Number of equivalent, parallel circuits
two-phase
2
liquid phase
1
76
Tables 4-3 and 4-4 list the heat exchanger parameters for this LG indoor unit and
outdoor unit, separately. The yellow region is for tube values, while orange is for fin
parameters. The blue region is other parameters that should be specified for the HPDM.
4.3 Case study 2: HPDM inputs for the manufacturing data
Based on Figure 3-26, there are in total five different kinds of inputs that should be
specified for the Heat Pump Design Model. Since we are utilizing the same LG indoor
and outdoor unit, the inputs of general system descriptions, compressor characteristics
and fin-and-tube heat exchanger parameters and configurations are the same as the lab
data inputs. The only differences for the manufactural data inputs are system refrigerant
side balancing, which should specify superheat temperature and subcooling temperature
used in the system, and the system operating conditions, which should include indoor and
outdoor dry-bulb temperature and wet-bulb temperature and air flow rates. Typically, the
manufacturers set the superheat temperature at a range of 8-12 F, while the subcooling
temperature range within a certain amount is 10-15 F. Those temperature inputs for
system operating conditions are shown in Tables 2-1 and 2-2 in section 2.3. The air flow
rates are 371 cfm for the indoor unit and 954 cfm for the outdoor unit.
77
4.4 Case study 1&2 results for laboratory and manufactural data by using HPDM
After required values are inputted into the Heat Pump Design Model, users can
obtain the simulation results and system performance data. In order to validate the test for
the HPDM in the mini-split heat pump system, performance output values are required to
be obtained for comparison. Therefore, the simulation results will include system cooling
capacity and heating capacity, EER, SHR, mass flow rate and power consumption for
both the cooling and heating modes. Appendix IX shows the simulation lab data results
for cooling mode and Appendix XII shows the simulation laboratory data results for
heating mode.
There are a total of 19 data sets for the laboratory testing data. Most of the
simulation procedures are reliable without system scaling in the cooling mode, but
system scaling was used when the outdoor dry-bulb temperature was 67 F because the
HPDM did not get a convergent result and showed a system internal error. As for the
heating mode, in order to get more accurate results, the scaling system for all of the 27
combinations of temperature conditions was applied and the results are presented in
Appendix XII. The HPDM manufactural data simulation results are presented in
Appendix XIII and Appendix XIV.
Since the manufacturer only provides some outputs related to the system capacity and
power consumption, the focus will be for outputs based more on these two performance
parameters. Therefore, two kinds of performance data are specified for this LG unit
regarding the simulation results of manufactural data within different temperature inputs
– system cooling or heating capacity and system power consumption.
78
After obtaining the simulation results for laboratory data and manufactural data for
both cooling mode and heating mode, detailed discussions are provided in the next
section.
4.5 Case studies discussions for simulation results for lab data and manufactural data
In this section, the results of two case studies are compared. The first case study is
the laboratory data comparison for cooling mode and heating mode. The second case
study is the manufactural data comparison for cooling mode and heating mode. The Heat
Pump Design Model cannot do all the time range speculations because there are large
relative errors for some temperature ranges, but the HPDM can be a generic benchmark
for most of the temperature conditions.
4.5.1 Case study 1: lab performance data comparison
In this case study, the cooling mode and the heating mode results have already been
provided to compare with the lab performance data which has been considered in the last
section. Cooling capacity, EER, SHR, mass flow rate and power consumption are
compared in Table 4-5.
Based on shown values of Table 4-5, the relative errors for capacities are in the
reasonable range and the absolute maximum relative error is 8.62%. However, the scaling
system capacity option was applied in the Heat Pump Design Model when simulating the
79
outdoor dry-bulb of 67 F, since the HPDM cannot converge at this temperature which is
typically too low for cooling mode. In the scaling system option, the cooling capacity was
set, as the lab data provided, within the capacity of 50 Btu/hr when the outdoor dry bulb
temperature was 67 F. The simulation results of SHR are very close to the actual values
and also for the mass flow rates, since the relative errors for these two parameters are
relatively small enough. The largest absolute relative error value is 5.11% for the SHR,
while 5.39% is the largest absolute relative error value for mass flow rate. The power
consumption prediction is considerably good in most of the temperature ranges except for
the outdoor dry-bulb temperature of 67 F, where relative errors for these are all over
10%. Also, because of Equation 4.1, the EER is the ratio of the capacity and power
consumption. Therefore, the relative errors of the EER are much larger when the  is
65 F. The reason for this situation is the temperature range of the compressor map, since
the temperature point of 65 F for the outdoor dry-bulb temperature is out of prediction
range. The compressor map is trustworthy for interpolation and defective for
extrapolation, thus the power consumption prediction is not accurate when the  is 65
F. Among those inaccurate simulation results for EER, only one point of EER is not
accurate, and that is when the outdoor dry-bulb temperature is 105 F. Here, the relative
error is 48.17%. This is because of data mistakenly recorded by the program. When the
relative errors are more than 10%, they are represented in red font.
EER =
 (/ℎ)
 ()
(4.1)
80
After Table 4-5 showing the relative errors for lab data outputs in cooling mode, five
figures are presented as follows. These figures are a graphic representation for the
relative errors of outputs for cooling capacity, EER, SHR, mass flow rate and power
consumption. In addition, the system charges and discharge pressures for every point of
the cooling mode are both in the reasonable range, while the suction pressures are in the
acceptable ranges except T  is 65 F, shown in Table 4-6.
Table 4-5 the relative errors for lab data outputs in cooling mode
Intended Intended Intended
Outdoor Indoor
Indoor Capacity
DryDryWetbulb
bulb
bulb
[F]
87
95
105
105
105
95
87
115
87
95
105
105
67
67
105
67
67
67
67
[F]
74
80
80
80
80
74
74
80
74
74
80
80
80
74
74
80
80
74
74
[F]
62
67
67
56
56
66
66
67
66
66
67
67
67
62
62
56
67
66
66
Btu/hr
EER
Sensible
Heat
Ratio
[Btu/Wh]
Mass
Flow
rate
Power
[lbm/hr]
W
5.35%
-0.68%
-2.58%
0.76%
3.40%
8.62%
3.60%
-3.65%
3.77%
2.44%
5.92%
5.00%
-3.91%
0.10%
-0.95%
1.28%
1.90%
-3.90%
-5.39%
-1.17%
2.18%
-0.36%
-3.20%
-3.73%
-2.12%
5.66%
-0.50%
-0.63%
3.37%
2.32%
6.21%
-3.61%
-0.20%
3.10%
4.62%
7.06%
-3.40%
-6.60%
-3.05%
-1.70%
6.18%
-5.90%
0.40%
3.57%
3.93%
7.98%
-5.17%
-0.50%
5.76%
2.18%
4.20%
-0.20%
-1.13%
-1.25%
-1.34%
2.58%
0.54%
-0.45%
-3.68%
-1.23%
-0.09%
27.30%
-1.20%
-0.78%
-19.01%
-0.07%
128.90%
-2.70%
-1.58%
-11.38%
3.18%
-48.17%
-3.90%
-5.82%
-0.13%
0.52%
14.77%
0.00%
-1.78%
-10.35%
-1.22%
-22.53%
0.10%
-4.30%
26.18%
-0.01%
4.64%
1.10%
-1.01%
-11.19%
-0.55%
13.45%
-0.50%
-0.46%
-13.29%
81
Figure 4-3 Cooling capacity comparison for lab data cooling mode
Figure 4-4 EER comparison for lab data cooling mode
82
5%
Figure 4-5 Mass flow rate comparison for lab data cooling mode
SHR comparison for lab data cooling mode
1.2
SHR (Predicted)
1
0.8
Actual
0.6
Predicted
0.4
Linear (Actual)
0.2
0
0
0.2
0.4
0.6
0.8
1
1.2
SHR (Actual)
Figure 4-6 SHR comparison for lab data cooling mode
83
Figure 4-7 Power consumption comparison for lab data cooling mode
Figure 4-3 shows the cooling capacity comparison for lab data in the cooling mode,
while Figure 4-4 presents the EER comparison. In addition, the Mass flow rate and SHR
relative errors are illustrated in Figure 4-5 and 4-6, respectively. Finally, Figure 4-7
shows the power consumption comparison for the lab data in the cooling mode. Based on
the representatives of these five figures, only when the outdoor temperature is 65 F, the
Heat Pump Design Model did not obtain good simulation results, which are shown
outside of the limitation line in these figures.
84
Table 4-6 Compressor suction, discharge pressure, and system charge
Intended Intended Intended
Outdoor
Indoor
Indoor suction pressure discharge pressure system charge
Dry-bulb Dry-bulb Wet-bulb
87
74
62
2.61%
-2.56%
-4.07%
95
80
67
5.70%
-1.37%
-1.86%
105
80
67
3.07%
-0.25%
-2.77%
105
80
56
-2.55%
-0.81%
-6.32%
105
80
56
-1.62%
-0.67%
-6.10%
95
74
66
5.76%
-1.34%
-2.68%
87
74
66
4.86%
-1.95%
-2.29%
115
80
67
3.21%
2.31%
2.16%
87
74
66
5.17%
-1.90%
-2.03%
95
74
66
5.76%
-1.34%
-2.68%
105
80
67
0.68%
-0.50%
-4.20%
105
80
67
-1.15%
-0.62%
-5.37%
67
80
67
7.24%
0.02%
-4.24%
67
74
62
-1.54%
-0.68%
-7.19%
105
74
62
11.46%
1.12%
-2.77%
67
80
56
-6.06%
-1.05%
-8.14%
67
80
67
-19.05%
-4.38%
-8.27%
67
74
66
21.68%
-5.35%
4.85%
67
74
66
20.83%
-4.62%
4.55%
85
Analysis of the cooling mode for lab data, the comparison of the laboratory data in
the heating mode is provided in the next step. The scaling system method was utilized for
all twenty-seven situations since the Heat Pump Design Model cannot create good results
for the heating capacity simulation. The relative error results for the lab data outputs for
the heating mode are shown in Table 4-7. Additionally, compressor suction, discharge
pressure, and system charge are all in Table 4-8.
Table 4-7 the relative error for lab data outputs in heating mode
Intended
Indoor
Dry-bulb
[F]
69.76
63.93
76.03
64.04
70.00
69.89
63.93
75.94
70.00
63.93
76.08
76.17
69.93
70.03
69.98
70.03
70.18
70.07
69.91
70.00
69.94
69.94
69.96
69.98
70.05
Indoor coil Intended Intended
cop
mass flow rate power
Inlet air
Outdoor Outdoor capacity
Wet-bulb Dry-bulb Wet-bulb
[F]
[F]
[F]
Btu/hr
lbm/hr
w
53.83
46.96
38.51
-0.05% -1.13%
10.39%
4.08%
50.88
62.17
49.63
0.88% -0.25%
5.22%
4.32%
58.15
62.02
49.26
-1.30% 3.97%
2.10%
-2.54%
51.31
68.07
53.08
-0.04% 4.36%
-1.02%
-1.61%
53.87
41.91
34.80
0.13% -0.77%
8.21%
3.29%
54.97
42.00
37.14
-0.35% -0.63%
7.65%
2.52%
51.98
34.09
29.23
-0.94% -1.02%
1.69%
2.12%
58.91
35.04
30.52
0.78%
4.63%
8.07%
-0.43%
54.99
61.90
51.21
0.91%
0.50%
10.38%
3.88%
48.03
46.59
61.88
1.46%
0.91%
2.79%
4.45%
53.91
47.85
61.97
-1.37% 6.51%
-1.25%
-3.51%
55.49
67.78
51.39
-0.24% 8.60%
-1.76%
-4.07%
52.56
67.91
51.22
-0.77% 10.85%
-4.77%
-6.10%
53.38
62.04
48.37
-0.11% 5.64%
-1.55%
10.31%
51.71
46.92
37.42
-1.14% -1.99%
8.83%
6.16%
51.75
47.03
37.42
-1.04% 6.23%
6.76%
-0.45%
53.24
41.97
40.50
-0.74% -1.66%
7.75%
4.75%
54.90
34.99
30.28
-0.57% 0.46%
6.26%
4.54%
51.31
26.92
23.10
-0.83% -0.27%
3.91%
2.88%
49.62
17.05
15.57
-0.09% 4.87%
-2.43%
0.04%
49.43
7.03
6.33
-0.60% 8.02%
-9.10%
-2.61%
49.80
34.93
27.69
-1.56% 0.32%
5.58%
4.53%
49.95
-2.92
-2.97
-1.86% 24.07%
-27.54%
-15.25%
51.64
46.84
39.09
-1.67% 6.51%
3.82%
-5.27%
51.62
34.98
29.89
-1.11% 4.67%
3.88%
-2.02%
86
Table 4-8 Compressor suction, discharge pressure, and system charge
Intended
Indoor
Dry-bulb
[F]
69.76
63.93
76.03
64.04
70.00
69.89
63.93
75.94
70.00
63.93
76.08
76.17
69.93
70.03
69.91
69.98
70.03
70.18
70.07
69.91
70.05
70.00
69.94
69.94
69.98
70.05
Intended
Indoor
Wet-bulb
[F]
53.834
50.882
58.154
51.314
53.87
54.968
51.98
58.91
54.986
48.0254
53.906
55.49
52.556
53.384
54.032
51.71
51.746
53.24
54.896
51.314
51.026
49.6166
49.4312
49.8038
51.638
51.62
Intended
Outdoor
Dry-bulb
[F]
47.0
62.2
62.0
68.1
41.9
42.0
34.1
35.0
61.9
61.9
62.0
67.8
67.9
62.0
62.0
46.9
47.0
42.0
35.0
26.9
27.1
17.0
7.0
34.9
46.8
35.0
Intended
Outdoor
Wet-bulb
F
38.5088
49.6256
49.262
53.078
34.8008
37.139
29.2262
30.5163
51.206
46.5872
47.8454
51.386
51.224
48.3692
48.6608
37.4234
37.4162
40.496
30.2833
23.1044
23.9162
15.5696
6.332
27.6872
39.092
29.894
suction
pressure
discharge
pressure
system
charge
-3.82%
-2.04%
-2.19%
1.85%
-5.70%
-8.97%
-13.60%
-5.54%
-0.87%
-1.97%
-1.90%
2.94%
4.59%
-3.30%
10.53%
-5.51%
-5.39%
-6.18%
-8.92%
-14.27%
-14.40%
-11.90%
-14.23%
-8.01%
-3.17%
-6.70%
-0.94%
0.28%
-0.44%
0.17%
-0.68%
-1.48%
-1.50%
-1.63%
0.38%
-0.89%
-0.97%
-2.57%
-2.39%
3.11%
-4.51%
-1.15%
-2.50%
-2.24%
-3.06%
-3.89%
6.91%
-11.71%
-11.39%
-2.43%
-1.99%
-3.84%
-5.43%
0.00%
-0.35%
-0.04%
-4.35%
-10.83%
-16.87%
-14.17%
-1.35%
-0.22%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
-7.22%
-8.70%
-13.04%
-8.70%
-13.04%
-17.39%
-17.39%
-11.57%
-4.35%
-4.35%
However, achieving this option in the HPDM, the simulation results for heating
capacity are all very similar to the actual ones and the relative errors for the heating
capacities are all in a reasonable range and they are all around 1% relative errors. There is
87
a data set where the prediction was not very accurate when the outdoor dry-bulb and wetbulb temperature is around -3 F. The HPDM cannot get good simulation results in the
heating mode when the outdoor temperature is very low. The simulation results include
the mass flow rate, power consumption, and COP prediction. The main reason for the
inaccurate simulation results is the limitation for a temperature range of the compressor
map which is directly related to the mass flow rate and power consumption. In addition,
the COP is the ratio of the heating capacity and the power consumption in the heating
mode, which is illustrated in Equation 4.2. If any of these two parameters is inaccurate,
the COP prediction will also be an inaccurate one. Therefore, the HPDM cannot get a
good simulation result when the outdoor dry-bulb and wet-bulb temperature is around -3
F. The Heat Pump Design Model is demonstrated to be good results for the simulating
heating mode in other temperature ranges for the high compressor speed. Since there are
limited data sets for low compressor speed and medium compressor speed, this study
focuses more on the high compressor speed data values.
COP =
 ()
 ()
(4.2)
88
Figure 4-8 Heating capacity comparison for lab data heating mode
COP comparison for lab data heating mode
5%
5.00
4.50
-5%
4.00
COP (Prdicted)
3.50
3.00
2.50
Actual
2.00
Predicted
1.50
Linear (Actual)
1.00
0.50
0.00
0.00
1.00
2.00
3.00
4.00
5.00
COP (Actual)
Figure 4-9 COP comparison for lab data heating mode
89
Power consumption comparison for lab data heating mode
2000
5%
Power consumption Predicted)
1800
1600
-5%
1400
1200
1000
Actrual
Predicted
800
Linear (Actrual)
600
400
200
0
0
500
1000
1500
2000
Power consumption (Actual)
Figure 4-10 Power consumption comparison for lab data heating mode
Mass flow rate comparison for lab data
heating mode 10%
180.00
-10%
Mass flow rate (Predicted)
160.00
140.00
120.00
100.00
Actrual
80.00
Predicted
60.00
Linear (Actrual)
40.00
20.00
0.00
0.00
50.00
100.00
150.00
200.00
Mass flow rate (Actual)
Figure 4-11 Mass flow rate comparison for lab data heating mode
90
There are four figures shown in 4-8, 4-9, 4-10 and 4-11, for the capacity comparison,
COP comparison, mass flow rate comparison and the power consumption comparison in
the heating mode simulation, respectively. They are the illustrations for these four key
outputs. Readers can determine deviation points for the heating mode lab data simulation
directly by looking at these figures.
4.5.2 Case study 2: manufactural performance data comparison
Comparisons between manufactural performance data and the simulation outputs for
the Heat Pump Design Model are also provided. In the beginning, the comparison will
concentrate on the cooling mode. In the next step, the heating mode comparison will be
offered in this section, too.
First, the cooling mode comparison is provided for the first step. The cooling
capacity and power consumption comparisons are the major topic to be discussed.
Table 4-9 Capacity relative error for manufacture data in the cooling mode
Outdoor
dry-bulb
temperature (F)
68
77
89.6
95
104
109.4
114.8
Capacity relative error
Indoor dry-bulb temperature (F)/ wet-bulb temperature (F)
68/57.2 71.6/60.8 77/64.4 80.6/66.2 86/71.6 89.6/75.2
0.50%
0.45%
0.04%
0.07%
-0.99%
-2.96%
-0.12%
0.40%
0.38%
0.44%
-0.01%
-1.60%
-0.97%
-1.16%
-0.64%
-0.53%
-1.09%
-1.89%
-1.60%
-2.15%
-1.84%
-0.69%
-1.40%
-2.26%
-3.26%
-1.78%
-4.51%
-4.28%
-3.66%
-4.07%
-4.35%
-5.26%
-6.08%
-6.46%
-5.67%
-5.98%
-5.55%
-6.73%
-7.94%
-8.13%
-7.99%
-7.98%
91
Table 4-10 Power consumption error for manufacture data in the cooling mode
Outdoor
dry-bulb
temperature (F)
68
77
89.6
95
104
109.4
114.8
Power consumption relative error
Indoor dry-bulb temperature (F)/ wet-bulb temperature (F)
68/57.2 71.6/60.8 77/64.4 80.6/66.2 86/71.6 89.6/75.2
40.5%
3.2%
-4.3%
-6.1%
-6.4%
-6.5%
45.9%
10.9%
3.2%
1.3%
-0.6%
-0.8%
22.2%
3.7%
-0.5%
-1.9%
-3.2%
-5.9%
15.5%
1.3%
-1.3%
0.2%
-3.5%
-6.0%
11.4%
2.4%
2.3%
2.6%
1.6%
-0.8%
18.2%
14.0%
14.9%
15.3%
14.4%
12.9%
38.1%
37.0%
40.5%
43.6%
44.6%
42.5%
Base on Table 4-9, the relative errors for cooling capacity are relatively small. The
maximum absolute relative error is 8.13% and another relative error is smaller than this
value. Illustrated on Table 4-10, the power consumption prediction for the manufactural
data describes good agreement in a certain temperature range, otherwise, the power
consumption does not have great simulation results. The optimal temperature ranges were
from 71.6 F to 89.6 F for the indoor dry-bulb temperature, 60.8 F to 75.2 F for the indoor
wet-bulb temperature, and 68 F to 104 F for the outdoor temperature. The HPDM will
give bad power consumption simulation results in other temperature conditions, which
are marked by the red font in Table 4-10. As discussed in the last case study, the reason
for this issue is the limited temperature range for the compressor map. In addition, figures
4-12 and 4-13 present the relative error bounds for the cooling capacity and the power
consumption for manufacturer data in the cooling mode within the different temperature
range inputs.
92
Figure 4-12 Cooling capacity comparison for manufactural data in the cooling mode
93
Figure 4-13 Power consumption comparison for manufactural data in the cooling mode
94
The heating mode comparisons are provided as below. According to Table 4-11, the
relative errors for the heating capacity is pretty small, while the power consumption
prediction can be large within a certain temperature range, except for the condition of
outdoor wet bulb temperatures being 5 F, 14 F, and 59 F. The reason for heating capacity
simulating well is that the scaling system capacity option is also utilized for all of the
heating modes in the manufactural data conditions. Simultaneously, the power
consumption prediction can work well when the outdoor wet-bulb temperature is from 23
F to 50 F and the indoor dry-bulb temperature is between 60.8 F and 75.2 F. Figures 414 and 4-15 show the heating capacity and power consumption error bounds for different
temperature conditions which are illustrated in the Table 4-11.
Table 4-11 Capacity and power consumption relative error for manufacture data in the
heating mode
Indoor unit
dry bulb
60.8
64.4
68
69.8
71.6
75.2
Indoor unit
dry bulb (F)
60.8
64.4
68
69.8
71.6
75.2
5
0.3%
0.5%
0.5%
0.6%
0.5%
1.7%
5
-24.7%
-23.2%
-20.9%
-19.7%
-18.8%
-19.0%
Heating Capacity relative error
outdoor unit wet bulb temperature (F)
14
23
32
42.8
50
0.3%
-0.5%
-3.0%
0.7%
0.1%
0.3%
0.2%
-3.5%
-0.7%
0.1%
0.0%
-0.8%
-3.8%
0.0%
-0.9%
-0.1%
0.3%
-3.7%
0.0%
-0.8%
0.0%
0.5%
-4.1%
-0.5%
-0.8%
0.5%
0.7%
-3.7%
-0.2%
0.0%
Power consumption relative error
outdoor unit wet bulb temperature (F)
14
23
32
42.8
50
-16.5%
-11.5%
-1.7% 4.1%
7.3%
-14.6%
-7.6%
-2.6% 2.1%
8.1%
-13.0%
-6.7%
-2.3% 5.7%
7.6%
-10.8%
-3.2%
-2.1% 6.0%
9.6%
-10.2%
-2.6%
-1.9% 5.2%
10.4%
-9.6%
-2.1%
-1.6% 7.1%
10.3%
59
0.0%
-0.1%
-0.2%
-0.1%
0.1%
-0.3%
59
16.6%
18.8%
22.8%
24.1%
24.3%
24.5%
95
Figure 4-14 Heating capacity comparison for manufactural data in the heating mode
The error bounds of the heating capacity comparisons are 5% for each temperature
situation. The horizontal axis represents actual heating capacity, while the vertical axis is
the predicted heating capacity. Every simulation result is within the 5% error bound for
heating capacity simulation.
96
Figure 4-15 Power consumption comparison for manufactural data in the heating mode
In the meantime, the power consumption prediction is not as good as the heating
capacity prediction. The points for the outdoor wet-bulb temperature being 5 F, 14 F, and
59 F are out of the error bounds, which are shown in Figure 4-15.
97
CHAPTER 5.
CONCLUSIONS AND FUTURE WORK
The Heat Pump Design Model is a useful web-based and free of charge software. In
theory, a physical model is the core of the HPDM, thus it can provide accurate simulation
results for both cooling and heating modes. In practice, there are several large projects
utilized in the split system funded by the U.S Department of Energy. In addition, there is
limited research about mini-split heat pump system. However, the physical model
requires complex input parameters and sometimes these parameters are not easily to
obtained. When users can figure out these input parameters, the HPDM can be a good
model. Therefore, it is possible to investigate the HPDM in order to generalize it for a
mini-split heat pump system.
There are two kinds of data sources offered in this study: the laboratory data and the
manufactural data. Further, these two data sets are provided for both cooling mode and
heating mode. The lab data is provided by studies from the Herrick lab at Purdue
University.
The methodology of the HPDM should be acknowledged by the user. There are five
kinds of input values which are general system descriptions, system refrigerant-side
balancing input, compressor characteristics, fin-and-tube heat exchanger parameters and,
configurations inputs and system operating conditions inputs. After inputting these
parameters mentioned above and finishing the simulating process, the Heat Pump Design
Model can generate several key outputs which are system capacity, power consumption,
mass flow rate, sensible heat ratio, system EER or COP, system charge, every key point
performance data and component sizing.
98
In order to be a generic benchmark for the mini-split heat pump system, the HPDM
needs to test several case studies. There are two case studies provided in this thesis. The
first one implements the lab data inputs for both cooling mode and heating mode. By
comparison between the lab performance data and simulation results in the cooling
capacity, EER, SHR, mass flow rate and system power consumption, the HPDM
produces good results for the cooling mode lab data, except for the condition of an
outdoor dry-bulb temperature of 65 F. In addition, the heating capacity, COP, mass flow
rate and power consumption parameter comparisons are illustrated in this thesis. These
parameters have good simulation results in the lab data heating mode, except for  and
 are -2.92 F and -2.97 F, respectively. The second case study compares manufactural
performance output and simulation results in system capacity and power consumption for
both cooling mode and heating mode. Capacity prediction is great for the temperature
range provided in Case study 2. However, the relative errors for power consumption are
relatively small when  is between 23 F and 50 F, and the  is from 60.8 F to 75.2
F for the heating mode. In addition, the HPDM works well in the combined temperature
range of 71.6 F/ 60.8 F~89.6 F/ 75.2 F for  / and 68 F ~104 F for  . Since the
study of the temperature range of the manufactural data is included in the temperature
range of the lab data, by combining these two case studies, the HPDM can be used as a
generic benchmark in the temperature range which is shown for the manufactural data for
cooling mode and heating mode.
Future studies may focus on power consumption predictions in low outdoor dry-bulb
temperatures below 68 F in the cooling mode. For the heating mode, the power
99
consumption should be studied in low  temperature ranges (< 23 F) and high 
temperature ranges (>50 F).
100
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https://en.wikipedia.org/wiki/Standard_deviation#cite_note-StatNotes-1
104
Appendix I Rotary Compressor Map with Rated Capacity as 7125 Btu/Hr
Tcond(F)
Tevap(F)
-15
90
2150
425
2.02
27.9
100
Btu/h
Watts
Amps
Lb/h
80
2190
403
1.91
28.6
110
120
130
140
-10
Btu/h
Watts
Amps
Lb/h
2580
414
1.97
32.8
2490
441
2.1
31.9
2400
468
2.22
30.9
-5
Btu/h
Watts
Amps
Lb/h
3020
424
2.02
37.5
2880
454
2.16
36.4
2740
485
2.3
35.3
2600
516
2.45
34.2
0
Btu/h
Watts
Amps
Lb/h
3510
431
2.06
42.7
3320
465
2.21
41.4
3130
499
2.37
40.2
2940
534
2.53
38.9
2750
569
2.7
37.5
5
Btu/h
Watts
Amps
Lb/h
4040
435
2.08
48.4
3800
473
2.25
47
3560
511
2.42
45.6
3320
550
2.6
44.1
3080
589
2.78
42.6
10
Btu/h
Watts
Amps
Lb/h
4620
437
2.09
54.7
4330
479
2.28
53.1
4040
521
2.46
51.5
3750
563
2.66
49.9
3450
606
2.85
48.2
3160
649
3.05
46.5
2870
693
3.25
44.7
15
Btu/h
Watts
Amps
Lb/h
5250
437
2.09
61.5
4910
483
2.29
59.8
4560
528
2.49
58
4220
575
2.7
56.2
3880
621
2.91
54.3
3530
668
3.12
52.4
3190
716
3.34
50.5
20
Btu/h
Watts
Amps
5930
434
2.08
5540
484
2.29
5140
533
2.51
4740
583
2.73
4350
634
2.96
3950
684
3.18
3560
736
3.41
105
Lb/h
68.9
67
65
63
61
58.9
56.8
25
Btu/h
Watts
Amps
Lb/h
6670
429
2.06
76.9
6220
482
2.29
74.7
5770
536
2.52
72.6
5320
590
2.76
70.4
4870
644
2.99
68.2
4420
698
3.23
65.9
3970
753
3.48
63.7
30
Btu/h
Watts
Amps
Lb/h
7460
421
2.03
85.4
6950
479
2.27
83.1
6450
536
2.52
80.7
5940
594
2.77
78.3
5440
652
3.02
75.9
4940
710
3.27
73.5
4440
769
3.53
71.1
35
Btu/h
Watts
Amps
Lb/h
8300
411
1.99
94.6
7740
472
2.25
92
7180
534
2.51
89.4
6620
595
2.77
86.9
6070
657
3.04
84.3
5510
719
3.31
81.6
4960
782
3.58
79
40
Btu/h
Watts
Amps
Lb/h
9200
399
1.95
104
8580
464
2.22
102
7970
529
2.49
98.7
7350
594
2.77
96
6740
660
3.05
93.2
6130
726
3.33
90.3
5520
793
3.61
87.5
45
Btu/h
Watts
Amps
Lb/h
10200
383
1.9
115
9480
452
2.18
112
8810
522
2.47
109
8140
591
2.76
106
7470
661
3.05
103
6810
731
3.34
99.6
6150
801
3.64
96.6
50
Btu/h
Watts
Amps
Lb/h
11200
366
1.84
126
10400
439
2.14
122
9710
512
2.43
119
8990
585
2.74
116
8260
659
3.04
113
7540
733
3.35
109
6820
807
3.66
106
55
Btu/h
Watts
Amps
Lb/h
12200
346
1.77
137
11500
423
2.08
134
10700
500
2.4
130
9890
577
2.71
127
9110
655
3.03
123
8330
732
3.35
120
7550
810
3.67
116
106
Appendix II Rotary Compressor Map with Rated Capacity as 11740 Btu/hr
Tcond(F)
Tevap(F)
-15
90
3740
735
3.5
48.3
100
Btu/h
Watts
Amps
Lb/h
80
3860
697
3.35
50
110
120
130
140
-10
Btu/h
Watts
Amps
Lb/h
4460
712
3.4
56.4
4270
755
3.57
54.4
4070
799
3.75
52.3
-5
Btu/h
Watts
Amps
Lb/h
5150
724
3.44
63.7
4880
773
3.64
61.5
4600
823
3.84
59.3
4320
873
4.04
56.9
0
Btu/h
Watts
Amps
Lb/h
5930
734
3.47
72
5580
789
3.69
69.6
5230
845
3.92
67.2
4860
901
4.15
64.6
4490
957
4.38
61.8
5
Btu/h
Watts
Amps
Lb/h
6800
740
3.49
81.3
6370
802
3.74
78.7
5940
863
3.99
76.1
5500
925
4.25
73.3
5050
988
4.51
70.3
10
Btu/h
Watts
Amps
Lb/h
7750
743
3.49
91.6
7240
811
3.77
88.8
6730
879
4.05
85.9
6220
947
4.34
82.9
5690
1020
4.62
79.8
5160
1090
4.91
76.5
4620
1150
5.2
73.1
15
Btu/h
Watts
Amps
Lb/h
8790
743
3.48
103
8200
817
3.79
99.8
7610
891
4.1
96.7
7020
966
4.41
93.5
6420
1040
4.72
90.2
5810
1120
5.04
86.7
5190
1190
5.36
83.1
20
Btu/h
Watts
Amps
9910
739
3.46
9250
820
3.8
8580
901
4.14
7910
982
4.47
7230
1060
4.82
6540
1140
5.16
5850
1230
5.51
107
Lb/h
115
112
108
105
102
97.9
94.1
25
Btu/h
Watts
Amps
Lb/h
11100
732
3.42
128
10400
819
3.79
125
9630
906
4.16
121
8880
994
4.52
118
8120
1080
4.89
114
7360
1170
5.27
110
6590
1260
5.64
106
30
Btu/h
Watts
Amps
Lb/h
12400
720
3.37
142
11600
814
3.77
138
10800
908
4.16
135
9930
1000
4.56
131
9100
1100
4.96
127
8260
1190
5.36
123
7410
1290
5.76
119
35
Btu/h
Watts
Amps
Lb/h
13800
704
3.3
157
12900
804
3.73
153
12000
905
4.15
149
11100
1010
4.58
145
10200
1110
5.01
141
9240
1210
5.44
137
8320
1310
5.87
133
40
Btu/h
Watts
Amps
Lb/h
15200
683
3.21
173
14200
791
3.67
169
13300
899
4.13
165
12300
1010
4.58
160
11300
1110
5.04
156
10300
1220
5.5
152
9310
1330
5.96
147
45
Btu/h
Watts
Amps
Lb/h
16800
658
3.11
190
15700
773
3.59
185
14600
887
4.08
181
13600
1000
4.57
177
12500
1120
5.06
172
11500
1230
5.55
167
10400
1350
6.04
163
50
Btu/h
Watts
Amps
Lb/h
18400
628
2.98
207
17200
750
3.5
203
16100
872
4.02
198
15000
993
4.54
194
13800
1120
5.06
189
12700
1240
5.58
184
11500
1360
6.1
179
55
Btu/h
Watts
Amps
Lb/h
20100
593
2.83
226
18900
722
3.38
221
17600
851
3.94
216
16400
980
4.49
212
15200
1110
5.04
207
14000
1240
5.59
202
12800
1370
6.14
196
108
Appendix III Rotary Compressor Map with Rated Capacity as 5300 Btu/hr
Tcond(F)
Tevap(F)
-15
90
1610
325
1.45
21
100
Btu/h
Watts
Amps
Lb/h
80
1670
307
1.34
22.1
110
120
130
140
-10
Btu/h
Watts
Amps
Lb/h
1960
316
1.38
25.1
1870
336
1.5
23.9
1770
357
1.62
22.7
-5
Btu/h
Watts
Amps
Lb/h
2280
322
1.42
28.5
2160
346
1.55
27.3
2030
369
1.67
26
1890
393
1.8
24.7
0
Btu/h
Watts
Amps
Lb/h
2640
327
1.45
32.3
2480
353
1.58
31
2310
379
1.72
29.6
2150
406
1.86
28.2
1980
433
1.99
26.8
5
Btu/h
Watts
Amps
Lb/h
3030
330
1.47
36.6
2830
359
1.61
35.2
2630
388
1.76
33.7
2430
417
1.9
32.2
2230
447
2.05
30.6
10
Btu/h
Watts
Amps
Lb/h
3470
332
1.49
41.2
3230
363
1.64
39.7
2990
395
1.79
38.1
2750
427
1.94
36.5
2510
459
2.1
34.9
2270
491
2.26
33.2
2030
524
2.41
31.4
15
Btu/h
Watts
Amps
Lb/h
3930
331
1.49
46.3
3660
366
1.65
44.6
3380
400
1.81
43
3110
435
1.97
41.3
2830
469
2.14
39.6
2560
504
2.3
37.8
2280
540
2.47
35.9
20
Btu/h
Watts
Amps
4440
329
1.49
4130
366
1.66
3820
403
1.83
3500
441
2
3190
478
2.17
2880
516
2.35
2560
554
2.52
109
Lb/h
51.7
50
48.3
46.5
44.6
42.8
40.8
25
Btu/h
Watts
Amps
Lb/h
4980
325
1.48
57.6
4630
365
1.66
55.8
4280
405
1.84
53.9
3930
445
2.02
52
3580
485
2.2
50.1
3230
526
2.38
48.1
2880
567
2.56
46.1
30
Btu/h
Watts
Amps
Lb/h
5570
320
1.46
63.9
5180
362
1.65
62
4790
405
1.84
60
4400
448
2.03
58
4020
491
2.21
56
3630
534
2.41
53.9
3240
577
2.6
51.8
35
Btu/h
Watts
Amps
Lb/h
6190
312
1.44
70.7
5760
357
1.64
68.6
5340
403
1.83
66.5
4910
448
2.03
64.4
4490
494
2.23
62.3
4060
540
2.43
60.1
3630
586
2.63
57.9
40
Btu/h
Watts
Amps
Lb/h
6850
303
1.41
77.8
6390
351
1.62
75.6
5920
399
1.82
73.5
5460
447
2.02
71.2
4990
496
2.23
69
4530
545
2.44
66.7
4070
594
2.65
64.4
45
Btu/h
Watts
Amps
Lb/h
7560
292
1.38
85.4
7050
343
1.59
83.1
6550
394
1.8
80.8
6050
445
2.01
78.5
5540
496
2.23
76.1
5040
548
2.44
73.7
4540
599
2.66
71.3
50
Btu/h
Watts
Amps
Lb/h
8310
279
1.33
93.4
7760
333
1.55
91
7220
387
1.78
88.6
6680
441
2
86.1
6130
495
2.22
83.6
5590
549
2.44
81.1
5050
603
2.67
78.6
55
Btu/h
Watts
Amps
Lb/h
9100
265
1.29
102
8510
321
1.51
99.3
7930
378
1.74
96.8
7350
435
1.97
94.2
6760
491
2.21
91.6
6180
548
2.44
89
5600
606
2.67
86.3
110
Appendix IV Rotary Compressor Map with Rated Capacity as 9163 Btu/hr
Tcond(F)
Tevap(F)
-15
-10
-5
0
5
10
15
20
25
Btu/h
Watts
Amps
Lb/h
Btu/h
Watts
Amps
Lb/h
Btu/h
Watts
Amps
Lb/h
Btu/h
Watts
Amps
Lb/h
Btu/h
Watts
Amps
Lb/h
Btu/h
Watts
Amps
Lb/h
Btu/h
Watts
Amps
Lb/h
Btu/h
Watts
Amps
Lb/h
Btu/h
Watts
Amps
Lb/h
80
3013
544
3
39
3481
556
3
44
4020
565
3
50
4628
573
3
56
5307
578
3
63
6049
580
3
71
6861
580
3
80
7735
577
3
90
8663
571
3
100
90
2919
574
3
38
3333
589
3
42
3809
603
3
48
4355
616
3
54
4972
626
3
61
5651
633
3
69
6400
638
3
78
7220
640
3
87
8117
639
3
98
100
0
0
0
0
3177
624
3
41
3590
642
3
46
4082
660
3
52
4636
674
3
59
5253
686
3
67
5940
695
3
75
6697
703
3
84
7516
707
3
94
110
0
0
0
0
0
0
0
0
3372
681
3
44
3793
703
3
50
4293
722
3
57
4855
739
3
65
5479
754
3
73
6174
766
3
82
6931
776
4
92
120
0
0
0
0
0
0
0
0
0
0
0
0
3504
747
3
48
3941
771
4
55
4441
796
4
62
5011
812
4
70
5643
827
4
80
6338
843
4
89
130
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
4027
851
4
60
4535
874
4
68
5104
890
4
76
5744
913
4
86
140
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3606
898
4
57
4051
929
4
65
4566
960
4
73
5143
983
4
83
111
30
35
40
45
50
55
Btu/h
Watts
Amps
Lb/h
Btu/h
Watts
Amps
Lb/h
Btu/h
Watts
Amps
Lb/h
Btu/h
Watts
Amps
Lb/h
Btu/h
Watts
Amps
Lb/h
Btu/h
Watts
Amps
Lb/h
9678
562
3
111
10771
549
3
123
11864
533
3
135
13112
514
2
148
14361
490
2
162
15688
463
2
176
9054
635
3
108
10068
628
3
119
11083
617
3
132
12254
603
3
144
13424
585
3
158
14751
564
3
172
8429
709
3
105
9366
706
3
116
10381
702
3
129
11395
692
3
141
12566
681
3
155
13737
664
3
169
7750
780
4
102
8663
788
4
113
9600
788
4
125
10615
780
4
138
11707
775
4
151
12800
765
4
165
7102
859
4
99
7961
866
4
110
8820
866
4
122
9756
874
4
134
10771
874
4
148
11864
866
4
162
6447
929
4
96
7212
944
4
107
8039
952
4
119
8976
960
4
130
9912
968
4
144
10927
968
4
158
5783
1007
4
93
6494
1022
5
104
7266
1038
5
115
8117
1054
5
127
8976
1061
5
140
9990
1069
5
153
112
Appendix V Scroll Compressor Map with Rated Capacity as 28999 Btu/hr
Tcond(F)
Tevap(F)
-15
90
7930
1750
8.46
101
100
Btu/h
Watts
Amps
Lb/h
80
9230
1600
7.44
112
110
120
130
140
-10
Btu/h
Watts
Amps
Lb/h
11200
1620
7.43
135
9900
1770
8.44
125
8670
1980
9.59
115
-5
Btu/h
Watts
Amps
Lb/h
13200
1640
7.42
158
11900
1790
8.41
149
10600
2000
9.54
140
9380
2250
10.9
131
0
Btu/h
Watts
Amps
Lb/h
15200
1640
7.4
181
13900
1800
8.38
173
12600
2010
9.49
165
11300
2270
10.8
157
9960
2590
12.3
146
5
Btu/h
Watts
Amps
Lb/h
17400
1630
7.38
204
16000
1800
8.35
197
14700
2020
9.44
190
13400
2280
10.7
183
11900
2590
12.2
173
10
Btu/h
Watts
Amps
Lb/h
19600
1620
7.34
229
18200
1800
8.3
222
16800
2020
9.39
216
15400
2280
10.6
210
13900
2590
12.1
200
12200
2960
13.9
187
10200
3400
15.9
169
15
Btu/h
Watts
Amps
Lb/h
21900
1610
7.29
255
20500
1790
8.26
249
19000
2010
9.33
243
17600
2270
10.6
237
16000
2590
12
229
14200
2950
13.8
217
12200
3390
15.8
199
20
Btu/h
Watts
Amps
24400
1590
7.24
22900
1780
8.2
21400
2000
9.27
19900
2270
10.5
18200
2580
12
16300
2940
13.7
14100
3370
15.7
113
Lb/h
282
277
272
266
258
247
230
25
Btu/h
Watts
Amps
Lb/h
27100
1560
7.17
311
25500
1760
8.14
306
23900
1990
9.21
302
22300
2260
10.4
297
20500
2570
11.9
289
18500
2930
13.6
278
16200
3340
15.6
262
30
Btu/h
Watts
Amps
Lb/h
30000
1530
7.08
342
28300
1740
8.06
338
26600
1970
9.14
334
24900
2240
10.4
329
23000
2550
11.8
322
20900
2910
13.5
311
18500
3320
15.4
296
35
Btu/h
Watts
Amps
Lb/h
33100
1500
6.99
376
31300
1710
7.98
371
29500
1950
9.07
368
27600
2220
10.3
363
25600
2530
11.7
357
23400
2890
13.4
347
20800
3290
15.3
331
40
Btu/h
Watts
Amps
Lb/h
36500
1460
6.88
412
34600
1680
7.89
408
32600
1930
8.98
404
30600
2200
10.2
400
28500
2510
11.6
394
26100
2870
13.3
384
23400
3270
15.2
369
45
Btu/h
Watts
Amps
Lb/h
40200
1420
6.75
452
38100
1650
7.78
447
36000
1900
8.89
444
33800
2180
10.1
440
31500
2490
11.6
434
29000
2840
13.2
424
26100
3240
15.2
409
50
Btu/h
Watts
Amps
Lb/h
44100
1370
6.61
494
41900
1620
7.66
490
39700
1880
8.79
486
37300
2160
10
482
34900
2470
11.5
476
32200
2820
13.1
467
29100
3210
15.1
452
55
Btu/h
Watts
Amps
Lb/h
48400
1330
6.45
541
46000
1580
7.53
536
43600
1850
8.68
532
41100
2140
9.95
528
38500
2450
11.4
522
35600
2800
13
512
32400
3180
15
498
114
Appendix VI Scroll Compressor Map with Rated Capacity as 56898 Btu/hr
Tcond(F)
Tevap(F)
-15
90
15600
3350
15.5
198
100
Btu/h
Watts
Amps
Lb/h
80
18200
3080
13.6
220
110
120
130
140
-10
Btu/h
Watts
Amps
Lb/h
22000
3110
13.6
265
19500
3400
15.4
245
17000
3770
17.5
227
-5
Btu/h
Watts
Amps
Lb/h
26000
3130
13.6
310
23400
3430
15.4
292
20900
3810
17.5
276
18400
4300
19.9
257
0
Btu/h
Watts
Amps
Lb/h
30000
3140
13.5
356
27400
3450
15.3
339
24800
3840
17.4
325
22300
4320
19.7
308
19500
4910
22.5
286
5
Btu/h
Watts
Amps
Lb/h
34200
3130
13.5
402
31500
3450
15.3
388
28900
3850
17.3
374
26200
4340
19.6
359
23400
4930
22.3
339
10
Btu/h
Watts
Amps
Lb/h
38500
3110
13.4
451
35800
3450
15.2
437
33100
3850
17.2
426
30300
4340
19.5
412
27300
4930
22.2
394
24000
5620
25.4
368
20100
6440
29.2
331
15
Btu/h
Watts
Amps
Lb/h
43200
3080
13.3
501
40300
3430
15.1
489
37500
3840
17.1
479
34600
4340
19.3
466
31400
4920
22
449
27900
5600
25.2
425
23800
6410
28.9
390
20
Btu/h
Watts
Amps
48100
3040
13.2
45100
3400
15
42100
3830
17
39000
4320
19.2
35700
4900
21.9
32000
5580
25
27700
6370
28.7
115
Lb/h
555
544
534
523
507
484
450
25
Btu/h
Watts
Amps
Lb/h
53400
2990
13.1
612
50200
3370
14.9
602
47000
3800
16.9
593
43800
4300
19.1
583
40300
4880
21.7
568
36300
5550
24.8
546
31800
6330
28.5
513
30
Btu/h
Watts
Amps
Lb/h
59100
2930
13
674
55700
3330
14.8
664
52300
3770
16.7
656
48900
4270
19
646
45100
4850
21.6
632
40900
5520
24.6
611
36200
6280
28.3
579
35
Btu/h
Watts
Amps
Lb/h
65200
2870
12.8
740
61600
3280
14.6
731
58000
3730
16.6
723
54300
4240
18.8
714
50300
4820
21.4
701
45900
5480
24.5
680
40800
6230
28.1
649
40
Btu/h
Watts
Amps
Lb/h
71900
2790
12.6
812
68000
3220
14.4
803
64200
3690
16.4
795
60200
4200
18.7
786
55900
4780
21.3
773
51200
5440
24.3
753
45800
6180
27.9
723
45
Btu/h
Watts
Amps
Lb/h
79100
2720
12.4
889
74900
3160
14.2
880
70800
3640
16.3
873
66500
4160
18.5
864
61900
4740
21.1
851
56900
5390
24.2
832
51200
6130
27.7
802
50
Btu/h
Watts
Amps
Lb/h
86900
2640
12.1
973
82400
3100
14
964
78000
3590
16.1
957
73400
4120
18.4
948
68500
4700
21
935
63100
5350
24
915
57100
6070
27.6
886
55
Btu/h
Watts
Amps
Lb/h
95300
2550
11.8
1060
90600
3040
13.8
1050
85800
3540
15.9
1050
80800
4080
18.2
1040
75600
4660
20.8
1030
69800
5300
23.9
1010
63400
6020
27.4
976
116
Appendix VII laboratory data inputs for cooling modes
Intended
Outdoor
Dry-bulb
[F]
87
87
95
105
105
105
95
87
115
87
95
105
105
67
67
105
67
67
67
67
Intended
Indoor
Dry-bulb
[F]
80
74
80
80
80
80
74
74
80
74
74
80
80
80
74
74
80
80
74
74
Intended
Indoor
Wet-bulb
[F]
67
62
67
67
56
56
66
66
67
66
66
67
67
67
62
62
56
67
66
66
Superheat
F
17.83
22.82
23.01
24.39
25.77
25.77
24.03
21.77
26.83
21.95
23.96
25.61
26.50
14.33
16.22
27.18
16.62
13.71
14.95
14.85
Subcooling
[F]
12.36
12.33
12.07
10.51
9.62
9.74
11.84
12.66
9.50
12.83
11.96
10.19
9.92
11.96
11.09
10.01
10.53
10.69
11.74
11.35
Indoor coil
Air volume
Flow rate
[cfm]
226.72
229.43
213.89
213.48
231.72
240.02
201.82
201.18
219.25
200.94
202.06
169.69
142.44
230.13
229.84
229.55
229.43
141.26
206.71
223.37
117
Appendix VIII laboratory performance data sets for cooling modes
Intended
Outdoor
Dry-bulb
[F]
Intended
Indoor
Dry-bulb
[F]
Intended
Indoor
Wet-bulb
[F]
Capacity
Btu/hr
EER
[Btu/W-h]
87
87
95
105
105
105
95
87
115
87
95
105
105
67
67
105
67
67
67
67
80
74
80
80
80
80
74
74
80
74
74
80
80
80
74
74
80
80
74
74
67
62
67
67
56
56
66
66
67
66
66
67
67
67
62
62
56
67
66
66
10341
8340
8412
8128
7674
7677
8176
8620
7476
8582
8135
7879
7640
7811
7401
7367
7349
8794
7725
7698
13.95
11.35
10.46
9.01
8.57
8.64
10.46
12.12
8.42
12.49
11.15
8.94
8.54
17.36
8.40
16.41
16.60
21.06
19.33
18.14
Sensible
Heat
Ratio
0.69
0.74
0.71
0.73
1.04
1.03
0.58
0.56
0.76
0.56
0.57
0.66
0.63
0.74
0.77
0.78
1.00
0.61
0.57
0.61
Refrigerant
Flow rate
[lbm/hr]
Power
[W]
140.48
111.16
116.60
120.28
114.99
114.88
113.19
114.16
117.90
113.45
112.33
117.26
114.31
91.82
87.48
109.26
87.66
108.05
91.32
90.72
778
754
823
919
901
901
811
749
1001
746
813
902
893
436
434
895
432
422
430
429
118
Appendix IX HPDM laboratory data outputs for cooling modes
Intended Intended Intended
Outdoor
Indoor
Indoor
Dry-bulb Dry-bulb Wet-bulb
[F]
[F]
[F]
87
87
95
105
105
105
95
87
115
87
95
105
105
67
67
105
67
67
67
67
80
74
80
80
80
80
74
74
80
74
74
80
80
80
74
74
80
80
74
74
67
62
67
67
56
56
66
66
67
66
66
67
67
67
62
62
56
67
66
66
Capacity
Btu/hr
EER
[Btu/W-h]
9491
8786
9137
8609
7772
7845
8639
9155
8004
9112
8784
8210
7837
7804
7396
7601
7387
8687
7724
7656
12.06
11.27
10.84
9.46
8.73
8.61
10.41
11.68
8.13
11.75
10.57
8.92
8.59
22.10
19.23
8.51
19.05
16.32
20.23
20.58
Sensible
Heat
Ratio
0.70
0.71
0.68
0.69
1.00
1.00
0.57
0.56
0.69
0.56
0.57
0.65
0.63
0.73
0.74
0.74
1.00
0.61
0.58
0.61
Refrigerant
Flow rate
[lbm/hr]
Power
W
122.40
112.00
121.00
120.40
108.80
110.60
117.00
117.70
114.30
117.50
118.80
115.80
110.10
91.10
83.70
105.10
86.10
103.40
90.40
86.60
787.1
779.4
843.1
910.1
890.1
881.6
830.0
783.6
984.0
775.3
830.7
890.4
882.4
353.1
384.6
893.8
387.3
532.5
381.9
372.0
119
Appendix X laboratory data inputs for heating modes
Intended
Indoor
Dry-bulb
[F]
69.76
63.93
76.03
64.04
70.00
69.89
63.93
75.94
70.00
63.93
76.08
76.17
69.93
70.03
69.91
69.98
70.03
70.18
70.07
69.91
70.05
70.00
69.94
69.94
69.96
69.98
70.05
Intended
Indoor
Wet-bulb
[F]
53.83
50.88
58.15
51.31
53.87
54.97
51.98
58.91
54.99
48.03
53.91
55.49
52.56
53.38
54.03
51.71
51.75
53.24
54.90
51.31
51.03
49.62
49.43
49.80
49.95
51.64
51.62
Intended
Outdoor
Dry-bulb
[F]
46.96
62.17
62.02
68.07
41.91
42.00
34.09
35.04
61.90
61.88
61.97
67.78
67.91
62.04
62.01
46.92
47.03
41.97
34.99
26.92
27.14
17.05
7.03
34.93
-2.92
46.84
34.98
Intended
Outdoor
Wet-bulb
F
38.51
49.63
49.26
53.08
34.80
37.14
29.23
30.52
51.21
46.59
47.85
51.39
51.22
48.37
48.66
37.42
37.42
40.50
30.28
23.10
23.92
15.57
6.33
27.69
-2.97
39.09
29.89
Superheat
F
8.59
9.87
10.23
9.14
14.17
13.97
19.18
10.79
10.49
m
7.82
6.75
6.43
-0.25
9.69
9.17
9.40
6.83
1.54
4.62
2.22
10.77
5.62
3.64
1.53
16.38
1.60
Subcooling
[F]
18.00
11.22
7.04
8.26
15.10
14.29
18.14
15.07
5.68
19.64
16.16
15.87
18.86
2.42
27.38
20.03
11.34
22.45
23.13
30.28
7.23
29.66
28.60
11.85
26.59
21.51
18.77
Indoor coil
Air volume.
Flow rate
[cfm]
225
232
224
228
229
227
229
228
229
229
229
230
230
146
186
229
148
228
230
230
147
229
229
187
230
185
187
120
Appendix XI laboratory performance data sets for heating modes
Intended Intended Intended Intended
Indoor
Indoor
Outdoor Outdoor
Refrigerant
Dry-bulb Wet-bulb Dry-bulb Wet-bulb Capacity COP
Flow rate
[F]
[F]
[F]
F
Btu/hr [W/W]
[lbm/hr]
2.96
69.76
53.83
46.96
38.51
11267
137.24
3.69
63.93
50.88
62.17
49.63
12420
155.29
3.09
76.03
58.15
62.02
49.26
11673
157.30
3.72
64.04
51.31
68.07
53.08
12922
165.90
2.87
70.00
53.87
41.91
34.80
11137
133.45
2.86
69.89
54.97
42.00
37.14
11147
134.33
2.33
63.93
51.98
34.09
29.23
13720
157.83
2.20
75.94
58.91
35.04
30.52
11130
135.19
3.35
70.00
54.99
61.90
51.21
11741
152.38
48.03
46.59
3.64
63.93
61.88
12785
155.95
53.91
47.85
3.13
76.08
61.97
12117
156.66
3.85
76.17
55.49
67.78
51.39
10004
126.52
4.23
69.93
52.56
67.91
51.22
10114
123.17
2.62
70.03
53.38
62.04
48.37
10209
163.74
2.99
69.91
54.03
62.01
48.66
10769
127.16
3.17
69.98
51.71
46.92
37.42
10687
129.65
2.46
70.03
51.75
47.03
37.42
9203
130.01
2.85
70.18
53.24
41.97
40.50
11888
142.46
2.31
70.07
54.90
34.99
30.28
12144
146.43
2.09
69.91
51.31
26.92
23.10
12816
143.10
1.68
70.05
51.03
27.14
23.92
10083
152.12
1.97
70.00
49.62
17.05
15.57
11311
125.55
1.87
69.94
49.43
7.03
6.33
9824
107.59
2.85
69.94
49.80
34.93
27.69
7643
101.06
1.74
69.96
49.95
-2.92
-2.97
8367
90.68
2.74
69.98
51.64
46.84
39.09
10578
131.09
2.23
70.05
51.62
34.98
29.89
10588
136.03
Power
W
1084
958
1078
990
1112
1118
1688
1435
993
990
1088
729
668
977
1005
939
1029
1177
1458
1741
1395
1599
1452
737
1315
1103
1340
121
Appendix XII HPDM laboratory data outputs for heating modes
Intended Intended Intended Intended
Indoor
Indoor
Outdoor Outdoor
Refrigerant
Dry-bulb Wet-bulb Dry-bulb Wet-bulb Capacity COP
Flow rate Power
[F]
[F]
[F]
F
Btu/hr [W/W]
[lbm/hr]
W
69.76
53.834
47.0
38.5088
11261
2.926
151.5
1128
63.93
50.882
62.2
49.6256
12529
3.676
163.4
998.9
76.03
58.154
62.0
49.262
11521
3.213
160.6
1051.1
64.04
51.314
68.1
53.078
12916
3.885
164.2
974.4
70.00
53.87
41.9
34.8008
11152
2.846
144.4
1148.3
69.89
54.968
42.0
37.139
11108
2.841
144.6
1145.8
63.93
51.98
34.1
29.2262
13591
2.311
160.5
1723.7
75.94
58.91
35.0
30.51626 11217
2.301
146.1
1428.7
70.00
54.986
61.9
51.206
11848
3.366
168.2
1031.7
63.93
48.0254
61.9
46.5872
12972
3.675
160.3
1034.5
76.08
53.906
62.0
47.8454
11950
3.337
154.7
1049.5
76.17
55.49
67.8
51.386
9980
4.182
124.3
699.4
69.93
52.556
67.9
51.224
10036
4.688
117.3
627.5
70.03
53.384
62.0
48.3692
10198
2.77
161.2
1078
69.91
54.032
62.0
48.6608
10824
3.698
127
857.8
69.98
51.71
46.9
37.4234
10565
3.107
141.1
997
70.03
51.746
47.0
37.4162
9107
2.608
138.8
1024
70.18
53.24
42.0
40.496
11800
2.806
153.5
1232.5
70.07
54.896
35.0
30.28334 12075
2.322
155.6
1523.9
69.91
51.314
26.9
23.1044
12709
2.08
148.7
1790.6
70.05
51.026
27.1
23.9162
10143
1.814
142.2
1638.8
70.00
49.6166
17.0
15.5696
11301
2.071
122.5
1599.2
69.94
49.4312
7.0
6.332
9765
2.024
97.8
1414
69.94
49.8038
34.9
27.6872
7524
2.864
106.7
769.9
69.96
49.9496
-2.9
-2.974
8211
2.159
65.7
1114.5
69.98
51.638
46.8
39.092
10401
2.918
136.1
1045
70.05
51.62
35.0
29.894
10470
2.337
141.3
1313.3
122
Appendix XIII HPDM manufactural data outputs for cooling modes
Simulation manufactural data Power consumption (W)
Indoor unit
Outdoor unit dry bulb temperature (F)
wet bulb (F) dry bulb (F)
68
77
89.6
95
104
109.4
57.2
68
547.8
598.1
672
704.7
746.1 780.4
60.8
71.6
546.8
598.8
674.1
708.9
747.5 786.9
64.4
77
545.5
598.6
676.3
711
757.3
793
66.2
80.6
544.9
597.6
677.1
711.7
758.9 795.6
71.6
86
542.9
596.6
677.7
713.9
762.3 800.9
75.2
89.6
542.1
595.5
677.8
714.6
763.7 801.8
Simulation manufactural data capacity (Btu/hr)
Indoor unit
Outdoor unit dry bulb temperature (F)
wet bulb (F) dry bulb (F)
68
77
89.6
95
104 109.4
57.2
68
8881
8452
7839
7554
7130 6853
60.8
71.6
9425
9010
8364
8046
7742 7273
64.4
77
9933
9555
8950
8608
8048 7723
66.2
80.6
10209
9835
9232
8946
8329 7947
71.6
86
10912
10610
9989
9689
9138 8755
75.2
89.6
11225
10978
10410
10138 9623 9239
114.8
814.7
822.1
828.9
832.9
838.4
840.7
114.8
6574
6969
7381
7617
8351
8854
123
Appendix XIV HPDM manufactural data outputs for heating modes
Indoor unit
dry bulb
60.8
64.4
68
69.8
71.6
75.2
Indoor unit
dry bulb (F)
60.8
64.4
68
69.8
71.6
75.2
Simulation manufactural data capacity (Btu/hr)
outdoor unit wet bulb temperature (F)
5
14
23
32
42.8
50
8800
9229
10002
10393
11988
12574
8725
9240
9993
10334
11718
12438
8711
9246
9991
10273
11704
12212
8639
9240
10026
10246
11640
12216
8624
9243
9987
10213
11477
12217
8546
9176
9899
10154
11438
12112
Simulation manufactural data power consumption (W)
outdoor unit wet bulb temperature (F)
5
14
23
32
42.8
50
653.1
710
725.7
806.1
916.5
987.4
670.9
739.3
752.6
828.1
918.6
1005.7
698.9
791.4
780.4
850.4
972.2
1022.3
712.7
796.5
799.6
861.7
985.5
1041.6
725.5
829.9
810.3
872.7
988.6
1060.1
746
840.7
827.3
895.2
1017.5
1070
59
13650
13604
13590
13538
13419
13238
59
1142.2
1176.5
1216
1228.7
1231
1245
124
APPENDIX XV lab data suction, discharge pressure and system charge for cooling mode
Intended
Outdoor
Dry-bulb
[F]
87
95
105
105
105
95
87
115
87
95
105
105
67
67
105
67
67
67
67
Intended
Indoor
Dry-bulb
[F]
74
80
80
80
80
74
74
80
74
74
80
80
80
74
74
80
80
74
74
Intended
Indoor
Wet-bulb
[F]
62
67
67
56
56
66
66
67
66
66
67
67
67
62
62
56
67
66
66
suction pressure
discharge pressure
system charge
[psi]
114.61
122.14
127.78
122.63
122.79
118.41
117.50
129.45
117.05
118.41
124.95
122.01
120.29
114.57
118.16
113.90
134.16
119.00
117.93
[psi]
349.98
386.82
429.46
424.96
424.96
384.21
351.14
477.76
351.28
384.21
427.43
425.25
265.85
262.08
423.66
260.34
269.92
264.55
262.52
[lb]
2.31
2.31
2.31
2.31
2.31
2.31
2.31
2.31
2.31
2.31
2.31
2.31
2.31
2.31
2.31
2.31
2.31
2.31
2.31
125
APPENDIX XVI HPDM results for lab data suction, discharge pressure and system charge for
cooling mode
Intended
Outdoor
Dry-bulb
[F]
87
95
105
105
105
95
87
115
87
95
105
105
67
67
105
67
67
67
67
Intended
Indoor
Dry-bulb
[F]
74
80
80
80
80
74
74
80
74
74
80
80
80
74
74
80
80
74
74
Intended
Indoor suction pressure discharge pressure
Wet-bulb
[F]
[psi]
[psi]
62
117.6
341
67
129.1
381.5
67
131.7
428.4
56
119.5
421.5
56
120.8
422.1
66
125.4
379.5
66
123.2
344.3
67
133.6
488.8
66
123.1
344.6
66
125.5
379.8
67
125.8
425.3
67
120.6
422.6
67
108.6
258.1
62
144.8
250.4
62
131.7
428.4
56
107
257.6
67
108.6
258.1
66
144.8
250.4
66
142.5
250.4
system charge
[lb]
2.216
2.267
2.246
2.164
2.169
2.248
2.257
2.36
2.263
2.253
2.213
2.186
2.119
2.422
2.246
2.122
2.119
2.422
2.415
126
APPENDIX XVII lab data suction, discharge pressure and system charge for heating mode
Intended Intended Intended Intended
Indoor
Indoor Outdoor Outdoor
DryWetDrybulb
bulb
bulb
Wet-bulb
[F]
[F]
[F]
[F]
69.76
53.834
47.0
38.5088
63.93
50.882
62.2
49.6256
76.03
58.154
62.0
49.262
64.04
51.314
68.1
53.078
70.00
53.87
41.9
34.8008
69.89
54.968
42.0
37.139
63.93
51.98
34.1
29.2262
75.94
58.91
35.0
30.51626
70.00
54.986
61.9
51.206
48.0254
46.5872
63.93
61.9
53.906
47.8454
76.08
62.0
76.17
55.49
67.8
51.386
69.93
52.556
67.9
51.224
70.03
53.384
62.0
48.3692
69.91
54.032
62.0
48.6608
69.98
51.71
46.9
37.4234
70.03
51.746
47.0
37.4162
70.18
53.24
42.0
40.496
70.07
54.896
35.0
30.28334
69.91
51.314
26.9
23.1044
70.05
51.026
27.1
23.9162
70.00
49.6166
17.0
15.5696
69.94
49.4312
7.0
6.332
69.94
49.8038
34.9
27.6872
69.98
51.638
46.8
39.092
70.05
51.62
35.0
29.894
suction
pressure
discharge
pressure
system
charge
[psi]
120.29
149.24
153.16
159.25
112.09
113.04
92.71
95.91
148.08
149.24
152.29
166.50
163.02
162.15
140.96
124.67
129.27
116.61
96.51
84.92
93.46
73.10
62.73
110.23
121.66
99.47
[psi]
462.67
442.66
502.70
458.32
452.08
454.11
488.63
491.82
458.47
466.73
518.51
460.64
430.18
526.34
517.64
446.43
517.93
486.31
494.43
526.92
500.24
485.88
447.15
405.96
503.72
506.33
[lb]
2.30
2.30
2.30
2.30
2.30
2.30
2.30
2.30
2.30
2.30
2.30
2.30
2.30
2.30
2.30
2.30
2.30
2.30
2.30
2.30
2.30
2.30
2.30
2.30
2.30
2.30
127
APPENDIX XVIII HPDM results for lab data suction, discharge pressure and system charge for
heating mode
Intended Intended Intended Intended
Indoor
Indoor Outdoor Outdoor
DryWetDryWetbulb
bulb
bulb
bulb
[F]
[F]
[F]
[F]
69.76
53.834
47.0
38.5088
63.93
50.882
62.2
49.6256
76.03
58.154
62.0
49.262
64.04
51.314
68.1
53.078
70.00
53.87
41.9
34.8008
69.89
54.968
42.0
37.139
63.93
51.98
34.1
29.2262
75.94
58.91
35.0
30.5163
70.00
54.986
61.9
51.206
48.0254
46.5872
63.93
61.9
53.906
47.8454
76.08
62.0
76.17
55.49
67.8
51.386
69.93
52.556
67.9
51.224
70.03
53.384
62.0
48.3692
69.91
54.032
62.0
48.6608
69.98
51.71
46.9
37.4234
70.03
51.746
47.0
37.4162
70.18
53.24
42.0
40.496
70.07
54.896
35.0
30.2833
69.91
51.314
26.9
23.1044
70.05
51.026
27.1
23.9162
70.00
49.6166
17.0
15.5696
69.94
49.4312
7.0
6.332
69.94
49.8038
34.9
27.6872
69.98
51.638
46.8
39.092
70.05
51.62
35.0
29.894
suction
pressure
discharge
pressure
system
charge
[psi]
115.70
146.2
149.8
162.2
105.7
102.9
80.1
90.6
146.8
146.3
149.4
171.4
170.5
156.8
155.8
117.8
122.3
109.4
87.9
72.8
80
64.4
53.8
101.4
117.8
92.8
[psi]
458.30
443.9
500.5
459.1
449
447.4
481.3
483.8
460.2
462.6
513.5
448.8
419.9
542.7
494.3
441.3
505
475.4
479.3
506.4
534.8
429
396.2
396.1
493.7
486.9
[lb]
2.18
2.3
2.292
2.299
2.2
2.051
1.912
1.974
2.269
2.295
2.3
2.3
2.3
2.3
2.3
2.3
2.134
2.1
2
2.1
2
1.9
1.9
2.034
2.2
2.2
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