MODELLING OF MOBILE AIR-
CONDITIONING SYSTEMS FOR
ELECTRIC VEHICLES B. Torregrosa , J. Payá, J.M. Corberán
4th European Workshop
MAC and Vehicle Thermal Systems 2011
Torino, December 2nd, 2011
Motivation
Objectives
Models
Results
Conclusions
Content
2
Recent support of electric vehicles (EVs) (EU: 7th Framework Programme, national EV development plans)
From NREL estimations, up to 20% increase in fuel consumption due to MAC in summer
Limited waste heat available from the EV motor (2-3 kW @ 40ºC) for heating and defogging in winter
Motivation
3
Motivation Objectives Models Results Conclusions
Need for:
Tools to assist MAC design
Efficient MAC technologies
MAC causes a large shortening of EV autonomy
ICE Project: develop an innovative Mobile Air Conditioning system for an EV
Magnetocaloric heat pump technology
Innovative design and control of the thermal power distribution loop
Objectives
4
Motivation Objectives Models Results Conclusions
Development of models to assist the design of MAC systems
Thermal load calculation
Heat pump and HEXs performance
Selection of equipment
Parametric studies
Optimisation of MAC system and EV autonomy
Overall model
5
Motivation Objectives Models Results Conclusions
HP EL
• Te, RHe
• Tdriv RHdriv
• Tpass RHpass
TAC
P v
I
INPUTS External conditions Speed (driving cycle) Control settings (target T)
MAIN OUTPUTS Car cabin temperature and RH AC outlets temperature Power consumption
TAC
Overall model
6
Motivation Objectives Models Results Conclusions
CABIN Cabin air T (multizone)
Cabin air RH (multizone)
HEAT PUMP
Supply air flow
Supply air T
Supply water flow
Supply water T
RADIATOR LOOP
Return water T
ELECTRICAL SYSTEMS
AMBIENT Air temperature
Air relative humidity Solar irradiation
Supply air RH
Ambient
Car speed
Amb. Car speed
Set point
Simulation of the car cabin’s thermal behaviour
Two zones: driver and passengers
Inertia of seats and car body
Cabin model
7
Motivation Objectives Models Results Conclusions
Gpass
Gdriv
Ge,pass
Ge,driv
DRIVER PASSENGERS
Gmass,pass
α·mAC,driv
(1-α)·mAC,driv
mdriv,pass
mψ
mAC,pass
I
mr,driv
mv
mAC,pass mpass,e
I·Seq,pass I·Seq,driv
I·Seq,b,pass I·Seq,b,driv
Q
0D model based on energy and mass balances.
Each zone: 4 differential equations
Cabin model
8
Motivation Objectives Models Results Conclusions
CAR BODY
DRIVER ZONE
Inertia of the car body
Heat transfer between car body
and cabin air
Heat transfer between car body
and outside air
Solar irradiation absorbed by the car
body
0D model based on energy and mass balances.
Each zone: 4 differential equations
Cabin model
9
Motivation Objectives Models Results Conclusions
CAR BODY
CABIN MASSES
DRIVER ZONE
Inertia of the cabin masses
Heat transfer between cabin masses and air
Solar irradiation absorbed by the
cabin masses
0D model based on energy and mass balances.
Each zone: 4 differential equations
Cabin model
10
Motivation Objectives Models Results Conclusions
CAR BODY
CABIN MASSES
CABIN AIR TEMPERATURE
DRIVER ZONE
Inertia of the cabin air
Supply air flow Return air flow Heat transfer between car body
and cabin air Heat transfer between cabin masses and air
Sensible load from passengers
Air flow between driver zone and
passengers zone due to stack effect
Air flow between driver zone and
passengers zone due to AC distribution
0D model based on energy and mass balances.
Each zone: 4 differential equations
Cabin model
11
Motivation Objectives Models Results Conclusions
CAR BODY
CABIN MASSES
CABIN AIR TEMPERATURE
CABIN AIR HUMIDITY
DRIVER ZONE
Change in cabin air humidity
Supply air flow humidity
Return air flow humidity
Water vapour from passengers (latent
load)
Humidity of the air flow due to stack
effect
Humidity of the air flow due to AC
distribution
Cabin model
12
Motivation Objectives Models Results Conclusions
Validation
Pasajeros
2 kW
2 kW
Detailed modeling of each
component using IMST-ART. Physical and performance
based models
Losses in pipes and valves
Assembling of single components to form the heat pump
Heat pump model
13
Motivation Objectives Models Results Conclusions
Efficient reversible heat pump for EV
Compressor scroll type
variable speed
Evaporator microchannel HEX refrigerant-to-air
Condenser brazed plate HEX
refrigerant-to-water
R134a
Liquid-to-suction HEX
Heat pump model
14
Motivation Objectives Models Results Conclusions
Efficient reversible heat pump for EV
INPUTS Secondary flows Secondary inlet T Control settings
MAIN OUTPUTS Secondary outlet T Power consumption Performance
P, COP
Tout,evap
Tout,cond
Assembling of single components to form the heat pump
COIL HE
Heat pump model
15
Motivation Objectives Models Results Conclusions
Heat exchangers Physical based 1D models IMST-ART PLATE HE
Heat pump model
16
Motivation Objectives Models Results Conclusions
Compressor Variable speed, scroll type
Performance based model
Compressor efficiency ε = f(rp, n)
Pressure ratio Speed (rpm)
Com
p. e
ff.
Volumetric efficiency
ηv = f(rp, n)
Pressure ratio Speed (rpm)
Vol
. eff.
VALIDATION
Heat pump model
17
Motivation Objectives Models Results Conclusions
Validation Winter
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
45.0
0 5 10 15 20 25 30 35 40 45Time [min]
Tem
pera
ture
[°C
]
T air radiatorT water T outlets
2000 rpm
3000 rpm4000 rpm
5000 rpm
6000 rpm
Externa Temperature 10.0°CFresh Air Mode
Air flow = 505 scm/h Water flow = 2 m3/h
TEST
IMST - ART
Max. dev. = 3.3%
Heat pump model
18
Motivation Objectives Models Results Conclusions
Validation Summer
Air flow = 505 scm/h Water flow = 2 m3/h
TEST IMST - ART
10.0
15.0
20.0
25.0
30.0
35.0
0 200 400 600 800Time [s]
Tem
pera
ture
[°C
]
Outlet mean
33.0 °C
17.5°CExternal Temperature 35.0 °CFresh Air Mode
Compressor at full speed
Air temperature = 17.1 ºC Deviation = 2.3%
Radiator loop model
19
Motivation Objectives Models Results Conclusions
Simulation of the external loop of the heat pump
INPUTS Heat to the external loop Coolant mass flow External conditions (T, RH) Speed (driving cycle)
MAIN OUTPUTS Supply and return temp. Radiator’s thermal power
Ts
Tr
• Te, RHe
v
Radiator loop model
20
Motivation Objectives Models Results Conclusions
Simulation of the external loop of the heat pump Inertia and losses
Effectiveness method
Sensible and latent processes
𝑄𝑄𝑟𝑟𝑟𝑟𝑟𝑟 = �̇�𝑚𝑟𝑟𝑎𝑎𝑟𝑟 · 𝜀𝜀∗ · �ℎ𝑟𝑟𝑎𝑎𝑟𝑟 _𝑎𝑎𝑖𝑖 − ℎ𝑠𝑠𝑟𝑟𝑠𝑠 _𝐼𝐼�
Radiator loop model
21
Motivation Objectives Models Results Conclusions
Radiator model Performance based model HEX can be scaled up or down
* ESDU 86018, Effectiveness – NTU Relationships for the Design and Performance Evaluation of Two-Stream Heat Exchangers (1991)
*
Results
22
Motivation Objectives Models Results Conclusions
Thermal load SUMMER
LOAD (kW) WINTER SUMMER
STEADY WARM UP – 1h STEADY COOL DOWN – 1h
Driv Pass Driv Pass Driv Pass Driv Pass
SENSIBLE 2.78 0.45 3.05 0.75
0.33 0.99 0.47 1.58
LATENT 0 0 0.04 0.24
TOTAL 3.23 3.80 1.60, SHR 83% 2.05
Outside: T=35ºC RH=60% I=0 Comfort: T=25ºC RH<50% 7 passengers + driver Full recirculation
Outside: T=0ºC I=0 Comfort: DRIV: T=20ºC PASS: T>10ºC 7 passengers + driver DRIV: Fresh air PASS: Full recirculation No dehumidification
WINTER
ICE PROJECT DESIGN
CONDITIONS
Results
23
Motivation Objectives Models Results Conclusions
Thermal load SUMMER
Outside: T=35ºC RH=60% I=0 Comfort: T=25ºC RH<50% Full occupancy Time to target: 1h
Outside: T=0ºC I=0 Comfort: DRIV: T=20ºC PASS: T>10ºC No passengers Time to target: 1h No dehumidification
WINTER
LOAD (kW) WINTER SUMMER
FRESH AIR 4.40 9.58 FULL RECIRCULATION 2.05 3.04
- 53% - 68%
HARDEST OCCUPANCY CONDITIONS
Results
24
Motivation Objectives Models Results Conclusions
Heat pump performance
Outside: T=0ºC I=0 Comfort: T=20ºC 7 passengers + driver Fresh air No dehumidification
WINTER: NEDC @ 0ºC/80%RH
Heating power : 5.12 kW Electric power : 1.65 kW COP 3.1
Energy consumption 0.54 kWh
kWh Autonomy Heat pump compressor 0.54 -7.7%
Electrical resistance 1.68 -24.0%
Magnetocaloric system
(expected) 0.27 -3.8%
Results
25
Motivation Objectives Models Results Conclusions
Heat pump performance
Outside: T=35ºC RH=60% I=0 Comfort: T=25ºC RH<50% 7 passengers + driver Full recirculation
SUMMER: NEDC @ 35ºC/60%RH
Cooling power : 2.84 kW Electric power : 0.78 kW COP 4.0
Energy consumption 0.25 kWh
kWh Autonomy Heat pump compressor 0.25 -3.6%
Magnetocaloric system
(expected) 0.13 -1.6%
Conclusions
26
Motivation Objectives Models Results Conclusions
A powerful but simple model of a Mobile Air-Conditioning system for an EV has been developed
The model shows very good agreement with experimental data from the IVECO Daily minibus
The results are very useful to predict the thermal load, heat pump performance and help with the sizing of the components
MAC has a great impact on the autonomy of EVs. Both the technologies and operating conditions must be chosen carefully: Efficient MAC technologies such as heat pumps: - 8 to 14% autonomy Air recirculation with efficient heat pumps: - 4% autonomy Expected results with magnetocaloric heat pump: - 2 to 4% autonomy
Next steps: Including auxiliary systems (pumps and fans) energy consumption Waste heat from electrical systems Magnetocaloric heat pump
THANK YOU FOR YOUR ATTENTION
4th European Workshop
MAC and Vehicle Thermal Systems 2011
Torino, December 2nd, 2011
