A national laboratory of the U.S. Department of Energy

Office of Energy Efficiency & Renewable Energy

National Renewable Energy Laboratory 

Innovation for Our Energy Future 

Battery Thermal Management 

System Design Modeling 

G.H. Kim and A. Pesaran 

Presented at the 22nd International Battery, Hybrid and 

Fuel Cell Electric Vehicle Conference and Exhibition (EVS-22) 

Yokohama, Japan 

October 23–28, 2006 

Conference Paper 

NREL/CP-540-40446 

November 2006 

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BATTERY THERMAL MANAGEMENT DESIGN 

MODELING 

Gi-Heon Kim 

Post Doctoral Researcher, National Renewable Energy Laboratory, 1617 Cole Blvd, 

Golden, Colorado 80401 USA, +1 303 275-4437, Fax: +1 303 275-4415, 

gi_heon_kim@nrel.gov 

AHMAD A. PESARAN 

Principal Engineer, National Renewable Energy Laboratory, 1617 Cole Blvd, Golden, 

Colorado 80401 USA, +1 303 275-4441, Fax: +1 303 275-4415, 

ahmad_pesaran@nrel.gov

Topics: 13. Batteries, 14. Battery Management System 

Keywords: HEV, Battery Model, Thermal Management, Li-ion Battery 

Abstract 

Battery thermal management is critical in achieving performance and extended life of batteries in 

electric and hybrid vehicles under real driving conditions. Appropriate modeling for predicting 

thermal behavior of battery systems in vehicles helps to make decisions for improved design and 

shortens the development process. For this paper, we looked at the impact of cooling strategies 

with air and both direct and indirect liquid cooling. The simplicity of an air battery cooling 

system is an advantage over a liquid coolant system. In addition to lower heat transfer coefficient, 

the disadvantage of air cooling is that the small heat capacity of air makes it difficult to 

accomplish temperature uniformity inside a cell or between cells in a module. Liquid cooling 

systems are more effective in heat transfer and take up less volume, but the added complexity and 

cost may outweigh the merits. Surface heat transfer coefficient, h, and the blower power for air 

cooling are sensitive to the hydraulic diameter of the channel (Dh). However, because of the 

added thermal resistances, h evaluated at cell surface is not as sensitive to the variation of Dh in a 

water/glycol jacket cooling system. Due to the high heat transfer coefficient at small Dh and large 

coolant flow rate, direct liquid cooling using dielectric mineral oil may be preferred in spite of 

high pressure loss in certain circumstances such as in highly transient large heat generating 

battery systems. Results of computational fluid dynamics (CFD) model simulation imply that 

capturing the internal heat flow paths and thermal resistances inside a cell using a sophisticated 

three-dimensional cell model are important for the improved prediction of cell/battery thermal 

behaviors. This paper identified analyses and approaches that engineers should consider when 

they design a battery thermal management system for vehicles. 

Introduction 

Temperature greatly affects the performance and life of batteries, so battery thermal control must 

be used in electric and plug-in hybrid electric vehicle under real driving conditions. In recent 

years, automakers and their battery suppliers have paid increased attention to battery thermal 

 1
management, especially with regard to life cycle and related warranty costs. A thermal 

management system could be designed with a range of methods, from “simple energy balance 

equations” to more “sophisticated thermal and computational fluid dynamics models.” Regardless 

of the method, the basic performance of the management system is dictated by the thermal design 

of each cell or module. 

Designing a battery thermal management system for given HEV/PHEV battery specifications 

starts with answering a sequence of questions: “How much heat must be removed from a pack or 

a cell?” “What are the allowable temperature maximum and difference?” “What kind of heat 

transfer fluid is needed?” “Is active cooling required?” “How much would the added cost be for 

the system?” etc. In order to find a high performance and cost effective cooling system, it is 

necessary to evaluate system thermal response and its sensitivity as a function of controllable 

system parameters. 

The diagram below shows the working flow chart of our battery thermal management modeling 

process. Cell characteristics (dimensions, geometry, electrochemistry), operating conditions 

(power load from the vehicle, ambient conditions), module/pack cooling strategy (active or 

passive, air or liquid cooling, flow rates and temperature duty cycle) are all input to the battery 

thermal design management model. The model uses these inputs to do component and system 

analysis to predict the thermal response of the design. Modifications to the design can then be 

evaluated to determine the optimum solution considering factors such as cost, volume, mass, and 

maintenance issues. 

Analysis and Results 

A typical parallel cell cooling system was investigated as an example study. Figure 1 presents the 

schematics of a system configuration and system thermal responses. Pressure loss in coolant 

channel (ΔP), coolant temperature change between channel inlet and outlet (ΔT1), and 

temperature difference between cell surface and coolant mean temperature (ΔT2) are chosen for 

 2
the system responses of interest. ΔP and coolant flow rate determine the required pump/blower 

power and size. ΔT1 is a parameter indicating cell temperature uniformity possibly achieved. ΔT2

is closely related to heat transfer coefficient, h, and shows how much the cell temperature would 

be higher than the coolant temperature. On the other hand, maximum cell surface temperature 

relative to coolant inlet temperature, ΔTmax= ΔT1+ ΔT2, can be used as a parameter for controlling 

the upper limit of cell temperature tolerance. 

P

x

T

x

ΔT2

ΔT1

ΔP

cell surface temperature

coolant mean temperature

pressure

Dcell

Lcell

Q

0.5Dh

mc

. . Dcell

Lcell

Q

0.5Dh

mc

. .

Figure 1: Schematics of a typical parallel cell cooling system and system responses 

Note that the cell internal temperature distribution and its maximum depend on the thermal paths 

and resistances inside a cell. Therefore, the shapes, materials, thermal connectivity of cell 

components and location of heat transfer are important for predicting cell internal temperatures. 

Detailed investigations into this topic have been covered in separated studies. The effects of using 

different types of coolants were examined here. (See Table 1 for the properties of the heat transfer 

fluids examined here; air and dielectric mineral oil for direct cooling, and water/glycol for jacket 

cooling.) We selected coolant mass flow rate ( ) and the hydraulic diameter of coolant 

channels (D

mc &

h) as system control parameters. In this example case study, the cell was specified to 

have a 50 mm diameter, a 100 mm length, and to generate 2 W of heat. 

Even though the heat transfer is enhanced in a turbulent flow regime, the required blower power 

greatly increases with laminar to turbulence flow-transition. Therefore, many heat exchanger 

applications are designed to be operated at laminar flow regimes. If the channel gap is much 

smaller than cell diameter, the following fully developed laminar flow relations can be applied to 

the presented system. 

cf Re = 24 (Eq. 1) 

Nu = 5.385 

where Re= VDh/ν, Nu= hDh/k and cf is friction coefficient. The Nuselt number is evaluated for 

constant heat flux wall boundary conditions. 

 

 3
Table 1: Properties of coolants typically used in battery cooling systems 

Figure 2 (a) shows the channel pressure losses p nit mass flow rate ) as a function of 

oolants

re

er u ( ΔP mc / &

the coolant channel hydraulic diameter of coolant channel for different c . Due to the large 

difference in kinematic viscosity, ΔP varies in very different ranges for each coolant fluid. ΔP is 

directly proportional to fluid kinematic viscosity (ν) and coolant mass flow rate (mc & ). If the cell 

diameter is much larger than Dh, ΔP becomes inversely proportional to Dh

3

. Therefo the channel 

pressure loss changes are very sensitive to Dh when it is small, especially for the high kinematic 

viscosity fluids. 

3 ~ m ΔP

h

c

D

& ν

 (Eq. 2) 

4 ~

h

c

h D

m

D

ΔP & ν − ∂

∂

Flow power requirements to overcome the channel friction loss were normalized by the square of 

coolant mass flow rate and compared for the different coolant systems in Figure 2(b). Due to the 

much smaller fluid density and consequently larger volumetric flow rate at given mass flow rate, 

the air cooling system requires much higher flow power for compensating channel friction loss 

than the other systems at the given coolant mass flow rate and channel height. Note that not only 

the coolant channel friction loss but also the system manifold friction head and the static pressure 

head make a significant contribution to the required pumping power in liquid cooling systems. 

1 2 3 4 5 6 7 8 10-1

100

101

102

103

104

Dh (mm)

Air

Mineral Oil

Water/Glycol

1 2 3 4 5 6 7 8 10-1

100

101

102

103

104

105

106

Dh (mm)

Air

Mineral Oil

Water/Glycol

Power/

mc

2 [W/(kgs-1)2] . Power/

mc

2 [W/(kgs-1)2] .

ΔP/mc [kPa/(kgs-1)] . ΔP/mc [kPa/(kgs-1)] . (a) (b)

Figure 2: (a) Channel pressure loss per unit mass flow rate as a function of the coolant channel 

hy w

Kinetic Viscosity ν (m 1.461e-5 5.6e-5 2.582e-6 2/s)

Thermal Conductivity k (W/m K) 0.0242 0.13 0.3892

Specific Heat cp (J/kg K) 1006.43 1900 3323

Density ρ (kg/m 1.225 924.1 1069 3)

Air Mineral Oil Water/Glycol

Coolant

Property

Kinetic Viscosity ν (m 1.461e-5 5.6e-5 2.582e-6 2/s)

Thermal Conductivity k (W/m K) 0.0242 0.13 0.3892

Specific Heat cp (J/kg K) 1006.43 1900 3323

Density ρ (kg/m 1.225 924.1 1069 3)

Air Mineral Oil Water/Glycol

Coolant

Property

Viscosity ν (m2 Viscosity ν (m /s) 2 Kinematic /s)

draulic diameter. (b) Flow power requirement for pressure loss normalized by square of mass flo

rate as a function of the coolant channel hydraulic diameter. 

 4
Variations of ΔT1 and ΔT2 are shown for m& c and Dh respectively in Figure 3. To achieve the 

temperature uniformity over a cell, it is preferred to keep coolant temperature change in the 

channel as small as possible. ΔT1 is inversely proportional to coolant heat capacity flow rate. 

Therefore, increasing mass flow rate is not as effective in reducing coolant temperature change in 

large flow rate cooling as it is in a small flow rate region. In other words, in small flow rate 

cooling, a little change in flow rate can greatly affect the coolant temperature change, and 

consequently cell temperatures (especially when air is used for the heat transfer medium that has 

small cp as compared in Figure 3). Water/glycol is the most preferred among the tested coolant 

materials for achieving temperature uniformity of cell/pack due to its large heat capacity. 

pc cm

ΔT &

1

1 ~ (Eq. 3) 

2

1 11 ~

p mc cm

ΔT

& & − ∂

∂

(a) (b)

0.5 1 1.5 2 2.5 3 3.5 4 0

0.5

1

1.5

2

2.5

3

3.5

4

Mass-Flow Rate (g/s)

Temperature (oC)

Coolant Temperature Increase

Air

Mineral Oil

Water/Glycol

1 2 3 4 5 6 7 8 0

1

2

3

4

5

6

7

8

Dh (mm)

Temperature (oC)

Temperature Difference Between Coolant & Cell Surface

Air

Mineral Oil

Water/Glycol

ΔT1 ΔT2

Figure 3: (a) Variation of coolant temperature change inside a system as a function of coolant mass 

flow rate. (b)Variation of temperature difference between coolant and cell surface as a function of 

hydraulic diameter of coolant channel. 

Temperature difference between coolant flow and cell surface, ΔT2, is linear to Dh with slope 

being proportional to 1/k as shown in Figure 3. Note that 0.7 mm jacket wall thickness and 0.05 

mm air layer were considered between cell surface and water/glycol coolant channel. Due to 

small thermal conductivity of air, ΔT2 rapidly increases with Dh in air cooling. Therefore, if a 

small ΔT2 (or large heat transfer coefficient) is required, it is recommended to use the smallest 

hydraulic diameter channel possible for air cooling. On the other hand, ΔT2 is not so sensitive to 

variations of Dh in water/glycol cooling system due to relatively large thermal conductivity. 

constD

k

ΔT h +

1

2 ~ (Eq. 4) 

Note that const is 0 for direct contact cooling in the relation shown above. 

The ΔT2 curve shown in Figure 3 also implies heat transfer coefficient, h, which is inversely 

proportional to ΔT2. h is plotted as a function of Dh in Figure 4. In steady state, high h lowers ΔT2

to reduce cell temperature. In unsteady heat transfer viewpoint, high h means fast heat removal 

from small temperature displacement, reducing the peak temperature of the cell. Therefore, high h

 5
smoothes out the cell temperature oscillations under transient heat generating conditions. The 

heat transfer coefficient evaluated at cell surface for water/glycol jacket cooling greatly decreases 

compared with the value it would be if direct contact cooling due to added thermal resistances 

between coolant and cell. The reduction is greater at small Dh. So, direct liquid cooling using 

mineral oil shows much higher h values than the other coolants at Dh <2~3 mm in the presented 

case. In spite of large pressure losses due to large ν and small Dh in this operating region, mineral 

oil cooling may be preferred for its high heat transfer coefficient in certain conditions. 

1 2 3 4 5 6 7 8

0

100

200

300

400

500

600

700

800

900

1000

Dh (mm)

h (W/m2K)

Heat Transfer Coefficient

Air

Mineral Oil

Water/Glycol

Water/Glycol, if direct contact

Figure 4: Variation of heat transfer coefficient as a function of coolant channel hydraulic diameter. 

Contours of maximum cell surface temperature relative to coolant inlet temperature, ΔTmax (=ΔT1+ 

ΔT2) are plotted as a function of coolant mass flow rate ( ) and hydraulic diameter of coolant 

channels (D

mc &

h) for different coolant systems. The values of ΔTmax in the air system are much higher 

compared with other fluid systems due to its small heat capacity and thermal conductivity. 

Contour lines for the air system, Figure 5(a), are dense and mostly aligned vertically at > ~ 1 

g/s. This means that ΔT

mc &

max is dominated by and sensitive to Dh in this operating region. On the 

other hand, the water/glycol jacket cooling system (Figure 5(c)) contour lines are almost 

horizontal at < ~ 2 g/s, and the line density is relatively sparse at > ~ 2 g/s. This means that 

ΔT

mc & mc &

max is not very sensitive to Dh, and that ΔTmax would not be a strict limiting design factor of the 

water/glycol system. The lowest value of ΔTmax appears in the mineral oil direct contact cooling 

system (Figure 5(b)) with a small Dh and large operating region. Note that great pressure loss 

occurs in that operation region. 

mc &

 6
(a) Air (b) Mineral Oil (c) Water/Glycol

Figure 5: Contours of maximum cell surface temperature relative to coolant inlet temperature 

An example of confining the operation zone to given conditions is shown in Figure 6. By drawing 

contour lines of required conditions, possible operating zones can be found. The colored area 

shown in Figure 6 represents the operating zone satisfying Re<2300, ΔP<110 Pa, ΔTmax<4.5 o

C

and ΔT1<1.5 o

C in an air cooling system. Laminar restriction of Reynolds number is to avoid 

excessive friction loss due to turbulence flow transition. Point A is the operating point for getting 

maximum h for given conditions. B is the lowest ΔTmax operating point, and C is the minimum 

pressure loss (ΔP) operating point. 

Figure 6: Confining the operation zone and parameter optimization to given conditions 

An operating point (Dh , ) = (2.2 mm, 1.33 g/s) which is close to point A in Figure 6, the 

maximum h operating point satisfying given limiting conditions, was selected and simulated for 

the air cooling system using an axi-symmetric computational fluid dynamics (CFD) model. The 

model geometry and mesh are presented in Figure 7. The model includes internal cell component 

materials and geometries. The cell core winding was treated as a continuous material having 

orthotropic properties according to layer directions. As specified previously, the cell is 50 mm in 

diameter, 100 mm in length and generates heat with a rate of 2 W at its core. Inlet air temperature 

mc &

Re=2300

Δ P=37 Pa

Δ P=110 Pa

Δ T1=1.5 oC

Δ Tmax=4.5 oC

Δ Tmax=3.43 oC

A

C

B

Re=2300

Δ P=37 Pa

Δ P=110 Pa

Δ T1=1.5 oC

Δ Tmax=4.5 oC

Δ Tmax=3.43 oC

A

C

B

1.6 1.8 2

2 2.2 2.2 2.4

2.4 2.6 2.6 2.8

2.8

3

3 3

3.2

3.2 3.2

3.4

3.4 3.4

3.6

3.6 3.6

3.8

3.8

3.8

4

4

4

4.2

4.2

4.2

4.4

4.4

4.4

4.6

4.6

4.6

4.8

4.8 4.8

5

5

5 5

5.2

5.2

5.2

5.4

5.4 5.4

5.6

5.6

5.6

5.8

5.8 5.8

6

6

6 6

6.2

6.2

6.2

6.4

6.4

6.4

6.6

6.6

6.6

6.8

6.8

6.8

7

7

7 7

7.2

7.2

7.2

7.4

7.4

7.4

7.6

7.6

7.6

7.8

7.8

7.8

8

8

8 8

8.2

8.2

8.2

8.4

8.4

8.4

8.6

8.6

8.8

8.8

9

9

9.2

9.2

9.4 9.69.8 1100.210.4 10.610.8 11

Dh(mm)

mass flow rate (g/s)

1 2 3 4 5 6 7 8 0.5

1

1.5

2

2.5

3

3.5

4

0.6

0.8

0.8

1

1

1

1.2

1.2

1.2

1.4

1.4

1.4

1.4

1.6

1.6

1.6

1.6

1.8 1.8

1.8

1.8

2 2

2

2.2 2.2 2.2

2.4 2.4 2.4 2.6 2.6 2.8 2.8 3 3 3.2 3 4

Dh(mm)

1 2 3 4 5 6 7 8 0.5

1

1.5

2

2.5

3

3.5

4 4

1

1

1.2

1.2

1.2

1.4

1.4

1.4

1.6 1.6 1.6 1.8 1.8 1.8 2 2 2 2 2 2.2

Dh(mm)

1 2 3 4 5 6 7 8 0.5

1

1.5

2

2.5

3

3.5

0

2

4

6

8

10

12

1.6 1.8 2

2 2.2 2.2 2.4

2.4 2.6

2.6 2.8

2.8

3

3

3

3.2

3.2 3.2

3.4

3.4 3.4

3.6

3.6 3.6

3.8

3.8

3.8

4

4

4

4.2

4.2

4.2

4.4

4.4

4.4

4.6

4.6 4.6

4.8

4.8 4.8

5

5

5 5

5.2

5.2

5.2

5.4

5.4

5.4

5.6

5.6

5.6

5.8

5.8 5.8

6

6

6 6

6.2

6.2

6.2

6.4

6.4

6.4

6.6

6.6

6.6

6.8

6.8

6.8

7

7

7 7

7.2

7.2

7.2

7.4

7.4

7.4

7.6

7.6

7.6

7.8

7.8

7.8

8

8

8 8

8.2

8.2

8.2

8.4

8.4

8.4

8.6

8.6

8.8

8.8

9

9

9.2

9.2

9.4 9.69.8 1100.210.4 10.610.8 11

Dh(mm)

mass flow rate (g/s)

1 2 3 4 5 6 7 8 0.5

1

1.5

2

2.5

3

3.5

4

0.6

0.8

0.8

1

1

1

1.2

1.2

1.2

1.4

1.4

1.4

1.4

1.6

1.6

1.6

1.6

1.8 1.8

1.8

1.8

2 2

2

2.2 2.2 2.2

2.4 2.4 2.4 2.6 2.6 2.8 2.8 3 3 3.2 3 4

Dh(mm)

1 2 3 4 5 6 7 8 0.5

1

1.5

2

2.5

3

3.5

4 4 12

1

1

1.2

1.2

1.2

1.4

1.4

1.4

1.6 1.6 1.6 1.8 1.8 1.8 2 2 2 2 2 2.2

Dh(mm)

1 2 3 4 5 6 7 8 0.5

1

1.5

2

2.5

3

3.5

0

2

4

6

8

10

 7
was set to 35 o

C. The other surfaces, except the channel/cell interface were set as thermally 

adiabatic boundaries. 

Figure 8 shows temperature distribution contours of the cell and cooling air. In the upper frame of 

the figure, radial-direction length scale is exaggerated to see the thermal development in the air 

channel. Cell surface temperature constantly increases in the axial direction as coolant air 

temperature increases. However, cell internal temperature distribution is determined by the 

thermal paths and thermal resistances inside a cell. The maximum temperature of 38.41 o

C

appears on the cell axis a little bit downstream from the cell center in the presented cell 

specification. 

Cell Core

Coolant Channel

Terminal

Can

Terminal Current Collector

Figure 7: Model geometry and mesh representing an axisymmetric cylindrical cell 

Figure 8: Temperature distribution contours of the cell and the air coolant channel 

(top: expanded view near can surface and coolant channel) 

 8
Axial distribution of air flow mean temperature, cell surface temperature and cell center-line 

temperature are presented in Figure 9. Coolant air temperature change, ΔT1, is computed as 1.50 o

C. The maximum cell surface temperature relative to inlet air temperature, ΔTmax, is 2.89 oC at 

the channel outlet. The highest battery temperature appears in the middle of the centerline of the 

cell and displaced from coolant inlet temperature by 3.41 o

C. Due to entrance effect, air 

temperature rapidly increases near the channel inlet. In the entrance region, the radial profiles of 

temperature and velocity at the cell/coolant interface have steep gradients representing higher 

heat flux and wall friction. Entrance effect is more clearly seen on the axial distribution of heat 

transfer coefficient (h) and heat flux shown in Figure 10. 

0 1 2 3 4 5 6 7 8 9 10

35

35.5

36

36.5

37

37.5

38

38.5

39

Axial Distance (cm)

Temperature (oC)

Air Mean Temperature

Cell Surface Temperature

Cell Temperature at Axis

Figure 9: Axial distribution of air flow mean temperature, cell surface temperature and cell centerline temperature 

0 1 2 3 4 5 6 7 8 9 10 0

50

100

150

200

250

Axial Distance (cm)

Heat Flux (W/m2

)

0 1 2 3 4 5 6 7 8 9 10 0

20

40

60

80

100

120

Axial Distance (cm)

Heat Transfer Coefficient (W/m2K)

Figure 10: Axial distribution of heat transfer coefficient and heat flux 

Heat transfer coefficient, h, at the cell surface has a larger value near the channel inlet, and 

consequently so does the heat flux. As the flow approaches fully developed, the value of h

converges to the constant value, 56.23 W/m2

K, which is slightly lower that the predicted value, 

59.24 W/m2

K, using the relations shown in Eq. 1. However, the mean value of h over the heat 

transfer surface has a little bit higher value, 60.96 W/m2

K, due to the entrance zone effect. One of 

 9
the reasons for this discrepancy comes from the fact that heat flux distribution is not quite 

constant along the axial distance. Heat flux decreases continuously with axial distance so that the 

cell surface temperature increases slowly compared to coolant air mean temperature as shown in 

Figure 9 (see the difference of slopes of two curves). 

System response parameters from different prediction methods are presented in Table 2. Even 

though ΔP is predicted to be a little bit higher in CFD analysis due to the entrance effect, the 

parameters are generally well matched between the prediction methods except for the maximum 

cell surface temperatures. The disagreement of ΔTmax mainly originates from the fact that CFD 

analysis can capture the axially decreasing heat flux from cell to air, which makes the axial 

gradient of cell surface temperature smaller than that of air temperature. This is because high 

conductivity materials inside a cell, such as the aluminum can, would transfer internal heat flow 

to make cell temperature more even. This result strongly implies that capturing the internal heat 

flow paths and thermal resistances inside a cell are important for the improved prediction of 

cell/battery thermal behaviors. 

Table 2: System response parameters - Two different prediction methods 

CFD 114.2 1.50 2.89 3.41 60.96

109.1 1.49 3.64 N/A 59.24 Fully Developed Flow Relations 

with Constant Heat Flux

h [W/m2K]

mean heat 

transfer 

coefficient 

ΔTcell [

oC]

maximum 

cell internal 

temperature 

to inlet air

ΔTmax [

oC]

maximum 

cell surface 

temperature 

to inlet air

ΔT1 [

oC]

coolant 

temperature 

change

ΔP [Pa]

channel 

pressure 

loss

CFD 114.2 1.50 2.89 3.41 60.96

109.1 1.49 3.64 N/A 59.24 Fully Developed Flow Relations 

with Constant Heat Flux

h [W/m2K]

mean heat 

transfer 

coefficient 

ΔTcell [

oC]

maximum 

cell internal 

temperature 

to inlet air

ΔTmax [

oC]

maximum 

cell surface 

temperature 

to inlet air

ΔT1 [

oC]

coolant 

temperature 

change

ΔP [Pa]

channel 

pressure 

loss

Cooling of a larger cell that has 50 mm diameter, 200 mm length and generates heat with a rate of 

4 W at the cell core was simulated for a direct air cooling system and a water/glycol jacket 

cooling system. Reducing channel height greatly increases heat transfer coefficient at cell surface 

in a direct contact air cooling system. But reducing the channel height is limited by the channel 

friction loss, which increases sensitively with decreasing Dh for a given coolant flow rate. On the 

other hand, in an indirect water/glycol liquid cooling system, channel height is not a sensitive 

factor affecting heat transfer coefficient at cell surface as it is in air systems, even though 

water/glycol channel friction loss is not as significant in magnitude as in air for a given coolant 

mass flow rate. But it is still recommended in a liquid cooling system to use a small gap coolant 

channel to reduce system weight and volume by minimizing the amount of coolant in a system 

operated at a given coolant flow rate. CFD analyses were carried out for a direct air cooling 

system operated at (Dh , ) = (2.2 mm, 1.33 g/s) and for a water/glycol jacket cooling system at 

(D

mc &

h , ) = (4.0 mm, 1.70 g/s) as shown in Figure 11. Inlet coolant temperatures were set to 35 mc & o

C. The results indicate that due to the large differences of coolant velocity and kinematic 

viscosity between the two systems, the air cooling system needs to compensate for a much larger 

pressure loss than the water/glycol liquid cooling system (221 Pa versus 7.68 Pa). 

 10
Dh= 2.2 mm

m& c= 1.33 g/s

Dh= 2.2 mm

m& c= 1.33 g/s

Dh= 4.0 mm

m& c= 1.70 g/s

Dh= 4.0 mm

m& c= 1.70 g/s

air water/glycol

jacket

Lcell = 200 mm

Dcell = 50 mm

Figure 11: Schematics of larger cell geometries and coolant channels 

Temperature distribution contours are shown for comparison in Figure 12. Even though the rate 

of heat removal from cell to coolant is the same for the two compared systems, air flow is rapidly 

heated compared with water/glycol due to the small heat capacity of air. In addition, the 

difference between coolant mean temperature and cell surface temperature is larger in the air 

cooling system because of the smaller heat transfer coefficient. Therefore, not only the maximum 

temperature but also the temperature non-uniformity inside a cell is larger in the air cooling 

system than in the water/glycol system. Temperature imbalance inside a cell is bigger in the air 

cooling system. Note that temperature contour-lines are distributed similarly inside a cell in both 

cases. This implies that internal heat flows are similar in both systems, and consequently that the 

internal heat paths and the thermal resistances are determining the relative temperature 

distribution inside a cell. 

aluminum can

jacket

cell core cell core

aluminum can

air

water/glycol

Figure 12: Comparison of temperature distribution contours between air cooled cell and water/glycol 

cooled cell 

 11
Axial temperature profiles of the air cooling system and the water/glycol system are compared in 

Figure 13 (a). Compared with the water/glycol liquid cooled cell, the maximum temperature on 

the cell axis in the air cooled cell appears near the channel exit. A larger temperature difference 

between each end of the cell shifts the maximum temperature location further downstream. Heat 

transfer coefficients at cell surfaces are plotted in Figure 13 (b) for both systems. 

surfcell TT coolant

q h −

′′ =

_

 (Eq 5) 

Thermal resistances of the jacket wall and air gap layer between the channel coolant and the cell 

surface were used to evaluate the heat transfer coefficient of the water/glycol cooling system. 

Temperature displacement between the channel surface and the cell surface in the water/glycol 

cooled cell shown in Figure 13 (a) is due to these added thermal resistances. The higher heat 

transfer coefficient of the water/glycol system leads to a smaller temperature difference between 

the coolant and cell surface as shown in Figure 13 (a) and Eq. 5. Even though the cell 

temperatures are distributed in different ranges in each system, the magnitudes of temperature 

differences between the cell center axis and the cell surface of the air cooled cell and the 

water/glycol cooled cell are not very different because the same cell specifications are assumed 

for both cases. 

0 2 4 6 8 10 12 14 16 18 20 0

20

40

60

80

100

120

140

160

180

200

Axial Distance (cm)

Heat Transfer Coefficient (W/m2K)

AIR

WATER/CLYCOL

133.2 W/m2K

56.1 W/m2K

0 2 4 6 8 10 12 14 16 18 20 35

36

37

38

39

40

41

Axial Distance (cm)

Temperature (oC)

Coolant Mean Temperature, AIR

Cell Surface Temperature, AIR

Cell Temperature at Axis, AIR

Coolant Mean Temperature, WATER/GLYCOL

Cell Surface Temperature, WATER/GLYCOL

Cell Temperature at Axis, WATER/GLYCOL

Channel Surface Temperature, WATER/GLYCOL

(a) (b)

center, AIR

center, WATER/GLYCOL

Figure 13: Axial profiles of temperatures (a) and heat transfer coefficients at cell surfaces (b) 

A serial cooling system may be preferred over a parallel cooling system for its simplicity of 

manifolding flow distribution in certain circumstances. The CFD simulation results shown in 

Figure 13 are simply extended to a six-cell serial cooling system and presented in Figure 14. 

Other heat exchanges among the cells such as conduction through electric connectors are ignored. 

Cell temperature differences in a module more rapidly increases in the air cooling system 

proportional to the number of cells connected serially with the coolant channel. Cell-to-cell 

temperature imbalance mainly comes from the coolant temperature change in coolant channels. 

Due to the low heat capacity of air, it is difficult to accomplish temperature uniformity inside a 

cell or between the cells in a module using air for cooling large or high heat generating cells. 

 12
0 20 40 60 80 100 120

35

40

45

50

55

60

Cooling Channel Distance (cm)

Temperature (oC)

Cell Centerline Temperature, AIR

Cell Centerline Temperature, WATER/GLYCOL

Coolant Temperature, AIR

Coolant Temperature, WATER/GLYCOL

Figure 14: Extended temperature profiles for a six-cell serial cooling system 

In order to investigate the time dependent thermal response of battery cooling systems, transient 

CFD analyses were carried out with a cell specified in Figure 7. An air cooling system and a 

mineral oil direct liquid cooling system were compared. The systems were operated with the 

same channel geometry and coolant mass flow rate, (Dh , ) = (2.2 mm, 1.33 g/s). Initially, each 

system was in steady state with a heat generation rate of 2 W. A system was heated using sudden 

heat generation (50 W) for 2 min. Then, the cell was cooled down to the initial steady state 

conditions. Coolant inlet temperatures were kept constant at 35 

mc &

o

C. 

Using steady state fully developed relationships shown in Eq.1, channel pressure losses (ΔP) are 

predicted as 109.1 Pa and 418.3 Pa for the air system and the mineral oil system respectively. On 

the other hand, heat transfer coefficients are predicted as 59.24 W/m2

K for the air cooled surface 

and 318.2 W/m2

K for the mineral oil cooled surface. The mineral oil direct contact liquid cooling 

system is expected to have a much higher heat transfer coefficient than the other coolant systems 

(direct air and indirect water/glycol) when it is operated at small channel (Dh) and large coolant 

flow rate ( ) at the expense of high pressure loss in the coolant channel. In addition, mineral oil 

has a higher heat capacity rate ( ) than air flow (2.53 J/Ks versus 1.34 J/Ks), which means it 

can remove the suddenly released heat from the cell with a smaller increase of coolant 

temperature. The simulation results showing the transient effect of using high h and a high heat 

capacity coolant system are presented in Figure 15 and Figure 16. 

mc &

pc & cm

 13
50

Figure 15: Time variation of heat transfer rates from the cell to the coolant 

The heat transfer rates from the cell to the coolant are compared in Figure 15. Due to higher heat 

transfer coefficient, released heat is more quickly removed from the mineral oil cooled cell. In a 

high h and high system, a large amount of heat can be transferred from cell to coolant with 

a small temperature increase of the cell while the coolant temperature does not change much. 

pc & cm

Time variations of mean temperature of the cell core and mean temperature of the coolant outlet 

temperature are shown in Figure 16 for both the air and the mineral oil cooling systems. In the 

mineral oil cooling system, the peak temperature is lower and the cool down time is shorter. The 

results imply that a high h system is preferred for limiting the maximum peak temperature of a 

cell and damping out the temperature oscillation in highly transient heat generating battery 

systems. 

Figure 16: Time variations of mean temperature of the cell core and the coolant outlet temperature 

0 5 10 15 20 25 30 35 40

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

Time (minute)

Temperature (oC)

Cell Core Mean Temperature, AIR

Coolant Outlet Mean Temperature, AIR

Cell Core Mean Temperature, MINERAL OIL

Coolant Outlet Mean Temperature, MINERAL OIL

0 5 10 15 20 25 30 35 40

0

5

10

15

20

25

30

35

40

45

Heat Transfer Rate from Cell to Coolant

Time (minute)

Heat Transfer RAte (W)

Air Cooling

Mineral Oil Liquid Cooling

Rate

internal heat generation rate

 14
Conclusions 

In order to achieve performance and cost effective cooling of a battery module/pack for electric 

or hybrid vehicles, the system thermal responses and their sensitivities are evaluated as a function 

of controllable system parameters (e.g. Dh and ). For given cell specifications, different types 

of coolant are examined: air cooling, direct contact liquid cooling using mineral oil, and (indirect) 

water/glycol jacket cooling system. Trade-off analysis has been performed to identify the 

optimum operating parameters of cooling systems with given design-limiting conditions. 

mc &

The simplicity of an air battery cooling system is an advantage over a liquid coolant system. Air 

cooling could have less mass, has no potential for leaks, needs fewer components, and could cost 

less. However, the heat transfer coefficient (h) of an air cooling system is lower than that of other 

coolant systems. Another drawback of an air system comes from its small heat capacity. Due to 

the small heat capacity of air, it is difficult to accomplish temperature uniformity inside a cell or 

between the cells in a module using air for cooling large or highly heat generating cells. The 

temperature difference between coolant air and cell surface (ΔT2) is sensitive to variations of Dh

due to small heat conductivity of air. h is inversely proportional to Dh, while pressure loss in 

channel (ΔP) is inversely proportional to Dh

3

. Therefore, increasing h by reducing Dh is limited by 

the required blower power. Reducing coolant air temperature change inside a system (ΔT1) by 

increasing flow rate ( ) is also limited by blower power and size. mc &

Liquid cooling systems are more effective in heat transfer and take up less volume, but the added 

complexity and cost may outweigh the merits. Maintenance and repair of a liquid cooled pack is 

more involved and costlier. Indirect liquid cooling, with jackets, is easer to handle than direct 

liquid cooling. A water/glycol solution for an indirect cooling system has much lower viscosity 

than dielectric mineral oil for direct liquid cooling. Therefore, increasing the coolant flow rate 

may not be as severely restricted by the pump power as it is in a mineral oil direct cooling system. 

Water/glycol has a higher heat capacity. So, the coolant temperature change inside a system can 

be greatly reduced by using water/glycol as a heat transfer fluid in the system. This means that 

cell/module temperature uniformity can be effectively achieved even in a serial cooling system if 

the coolant paths are properly designed. Water/glycol solutions generally have a higher thermal 

conductivity than oil. However, due to the added thermal resistance between coolant and cell 

surface, such as jacket wall and air gap, the effective heat transfer coefficient at the cell surface is 

greatly reduced. Because of the added thermal resistances, h is not as sensitive to the variation of 

Dh. Since the coolant channel friction head is generally small, Dh is not a critical design parameter 

in a water/glycol system. A mineral oil direct contact liquid cooling system has a much higher 

heat transfer coefficient (h) than the other coolant systems when it is operated at small channel 

(Dh) and large coolant flow rate ( ) at the expense of high pressure loss in coolant channel. So, 

a mineral oil cooling system can be preferred for limiting the maximum peak temperature of a 

cell and damping out the temperature oscillation in certain circumstances such as in highly 

transient heat generating battery systems. 

mc &

CFD analysis captured the axially decreasing heat flux from cell to air which makes the axial 

gradient of cell surface temperature smaller than that of air temperature. This implies that 

capturing the internal heat flow paths and thermal resistances inside a cell using a sophisticated 

three-dimensional cell model is important for the improved prediction of cell/battery thermal 

behaviors. This paper identified analyses and approaches that engineers should consider when 

they design battery thermal management systems for vehicles. 

 15
Acknowledgments 

The U.S. Department of Energy (DOE), Office of the FreedomCAR and Vehicle Technology 

supported this effort. We appreciate the support provided by Dave Howell and Tien Duong of 

DOE. 

References 

V. Srinivasan and C.Y. Wang, “Analysis of Electrochemical and Thermal Behavior of Li-Ion Cells”,

Journal of Electrochemical Society, Vol. 150, ppA98-A106, 2003. 

J. N. Harb , V. H. Johnson and D. Rausen, “Use Of A Fundamentally Based Lead-Acid Battery Model In 

Hybrid Vehicle Simulations”, Proceedings of Annual Electrochemical Society Conference Seattle, 

Washington, Spring 1999. 

Ahmad Pesaran, “Battery Thermal Management in EVs and HEVs: Issues and Solutions”, Proceedings of 

Advanced Automotive Battery Conference, Las Vegas, Nevada, February 6-8, 2001 

Said Al-Hallaj, et. al, “Novel PCM Thermal Management Makes Li-Ion Batteries A viable Option for High 

Power Applications”, Battery Power Products and Technology Magazine, November 2004. 

Kojiro Ito, et al, “Development of Prismatic Type Nickel / Metal-Hydride Battery for HEVs”, Proceedings 

of the 20th Electric Vehicle Symposium, Long Beach, CA, November 2003. 

Shuichi Nagata, et. al, “Development of a New Battery System for Hybrid Vehicles” Proceedings of the 

20th Electric Vehicle Symposium, Long Beach, CA, November 2003. 

Authors 

Gi-Heon Kim, Post-Doctoral Researcher, National Renewable Energy Laboratory, 1617 

Cole Blvd, MS 1633, Golden, CO, 80401, telephone 303-275-4437, fax 303-275-4415, 

gi_heon_kim@nrel.gov

Dr. Gi-Heon Kim has worked as a post-doctoral researcher with the Advanced Vehicle 

Systems group at NREL since 2004. His recent research interests in advanced vehicle 

energy storage system tasks include development of a three dimensional Li-Ion battery 

thermal abuse model and HEV/EV battery thermal management system modeling. 

Another recent research topic is alternative fuel based diesel after-treatment systems. His expertise is in 

heat and mass transfer, fluid mechanics, turbulence, combustion, reacting flows and computational fluid 

dynamics. Dr. Kim completed a Ph.D. in Mechanical Engineering from Colorado State University with 

research on performance improvement of natural gas engines. In addition to his Ph.D., Dr. Kim holds an 

M.S. and B.S. in Mechanical Engineering from Seoul National University in Seoul, Korea. 

Ahmad Pesaran, Principal Engineer, National Renewable Energy Laboratory, 1617 Cole 

Blvd, MS 1633, Golden, CO, 80401, telephone 303-275-4441, fax 303-275-4415, 

ahmad_pesaran@nrel.gov

Dr. Pesaran joined NREL in 1983 and has been working on various energy systems such 

as solar cooling, ocean thermal energy conversion, air conditioning, desiccant 

dehumidification/cooling for buildings and buses, and most recently hybrid electric 

vehicles. Since 1995, he has been working on hybrid electric vehicle projects. He is 

currently the project manager for various activities related to battery thermal characterization, battery 

thermal analysis, and battery modeling and management. Dr. Pesaran holds a B.S. in chemical engineering 

from Shiraz University, as well as an M.S. in engineering and a Ph.D. in mechanical engineering from 

UCLA. He is a member of the FreedomCAR Electrochemical Energy Storage Technical Team.

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Battery Thermal Management System Design Modeling 

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Looks at the impact of cooling strategies with air and both direct and indirect liquid cooling for battery thermal 

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