Huang et al.

/ J Zhejiang Univ-Sci A (Appl Phys & Eng) 2013 14(6):417-426

417

Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering)

ISSN 1673-565X (Print); ISSN 1862-1775 (Online)
www.zju.edu.cn/jzus; www.springerlink.com
E-mail: jzus@zju.edu.cn

Simulation, experimentation, and collaborative analysis of

adjacent heat exchange modules in a vehicular cooling system*
Yu-qi HUANG1,2, Rui HUANG1, Xiao-li YU1, Feng LV1
(1Power Machinery and Vehicular Engineering Institute, Zhejiang University, Hangzhou 310027, China)
2

( Department of Mechanical and Aerospace Engineering, Monash University-Clayton, Victoria 3800, Australia)

E-mail: huangyuqi@zju.edu.cn

Received Jan. 30, 2013; Revision accepted Apr. 18, 2013; Crosschecked May 16, 2013

Abstract: A cooling system consisting of several heat exchange modules is a necessary part of an automobile, and its performance has a direct effect on a vehicles energy consumption. Heat exchangers, such as a charged air cooler (CAC), radiator, oil
cooler, or condenser have different structures and can be arranged in various orders, and each combination may produce different
effects because of interactions among them. In this study, we aimed to explore the principles governing interactions among adjacent heat exchangers in a cooling system, using numerical simulation and experimental technology. 3D models with different
combinations were developed, compared, and analyzed comprehensively. A wind tunnel test platform was constructed to validate
the computational results. We found that the heat dissipation of the modules was affected slightly by their relative position (the
rules basically comply with the field synergy principle), but was independent of the modules spacing within a certain distance
range. The heat dissipation of one module could be effectively improved by restructuring, but with a penalty of higher resistance.
However, the negative effect on the downstream module was much less than expected. The results indicated that the intensity of
heat transfer depends not only on the average temperature difference between cold and hot mediums, but also on the temperature
distribution.
Key words: Collaborative analysis, Heat exchangers, Field synergy principle, Computational fluid dynamics (CFD), Wind tunnel
doi:10.1631/jzus.A1300038
Document code: A
CLC number: TK172

1 Introduction
A cooling system is an important auxiliary system to ensure the operational stability of a vehicle. It
consists of several modules including a charged air
cooler (CAC), radiator, oil cooler, and condenser. All
heat exchanger modules are cooled successively by air,
the only cooling medium. With the growing demands
for fuel economy, automobile safety and comfort,
engine compartments have become more and more
crowded. The shape and size of a cooling system are
severely limited. Thus, with a single module already
designed for high efficiency, the spacing and position
*
Project (No. 51206141) supported by the National Natural Science
Foundation of China
Zhejiang University and Springer-Verlag Berlin Heidelberg 2013

of adjacent modules may have a significant effect on

the performance and size of the entire system.
Composite analysis of multi-heat exchangers in
cooling systems has been carried for several years.
There are complicated structures in a cooling system,
including pipes, plates, and tiny fins. To understand
the internal flow and heat transfer, a lot of resources
have been invested in numerical studies of vehicular
cooling systems. Asanuma et al. (1997) explored the
interaction between a radiator and a condenser. They
found that the condenser had significant negative effects on the performance of the radiator. Uhl et al.
(2001) adopted 3D computational fluid dynamics
(CFD) software to analyze the detailed flow in a radiator, condenser, and CAC, and coupled the simulated results with a flow solver. Their calculated results matched their measurements well. Kim and Kim

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(2008) predicted the performance of an engine cooling

module under various operating conditions using CFD
programs. The predicted air velocity before the radiator closely matched their test data. Juan (2008)
simulated the engine compartment of a truck, and
analyzed the influence on the internal flow of a number of factors including the grille, hood, bumper, radiator, fan size, blades, and arrangement. Their research indicated that the radiator had a major influence
on the flow resistance, and that torque decreased with
the application of optimized blades.
Experimentation has been widely used in research to overcome the limitation of computational
ability. Wind tunnel tests have been commonly used to
study many aspects of vehicular cooling systems, from
fins (Dong, 2007) to the entire system (Lv, 2010). Ngy
(1999) investigated the effects on cooling performance
of different radiator sizes, fan sizes, fan shrouds, and
fan speeds. A wind tunnel test system was established,
and the results from seven different vehicles were
compared. Ngy et al. (2002) studied the effects of
condenser size and position, and conducted a simulation based on experimental data. Khaled et al. (2012)
adopted particle image velocimetry (PIV), laser doppler velocimetry (LDV), and thermocouples to study a
vehicle under-hood cooling module. Flow and temperature distributions were clearly presented and a
new monitoring tool was developed.
With the development of computer technology
and test techniques, studies on cooling systems are
becoming more accurate, and have given valuable
results for reference. But most studies analyzed
multi-heat exchangers as a whole, and interactions
between heat exchangers have received less attention,
especially in experimental studies. This study focused
on the adjacent heat exchangers in a cooling system.
The cooling modules were modelled separately and
analyzed comprehensively, to explore the factors governing their interaction.
Because of their large size and heat transfer surfaces, the radiator and CAC were considered as the
main components of the vehicular cooling system. The
overall size of a cooling package is determined mainly
by the size and spacing of these two modules. For this
reason, the radiator and CAC modules were the main
focus of this paper. Commercial CFD codes based
upon the finite volume method were used to make the
simulation. Three modules with different combinations were simulated, compared, and examined using a

collaborative analysis, and the results were validated

with experimental data based on wind tunnel tests.

2 Methodology
2.1 Simulation description
The main research objects in this study were a
typical radiator (830 mm624 mm102 mm) and
CAC (800 mm605 mm162 mm) from a certain
engineering vehicle.
The CAC was a kind of plate-fin heat exchanger
with serrated fins on the hot-side and wavy fins on the
cold-side. It was arranged in front of the radiator because of its more critical cooling requirement. The
radiator was a traditional tube-fin heat exchanger
composed of flat tubes and wavy fins. 3D models were
established on the basis of actual production (Fig. 1).
Ambient air, as the cooling medium, flows through the
CAC and radiator in turn. The space between the
modules cores is about 35 mm. The height and width
of the channels are consistent with those of the actual
products. In considering the restricted computational
capability, the fins are omitted and simplified as a
porous medium. The channels are meshed with
hexahedral cells. The water and air tanks are meshed
with unstructured tetrahedral mesh. We identified a
cell size from 0.5 mm to 3 mm after a gridindependent test. About 8.3 million mixture elements
were generated for the models.
According to the actual testing conditions, the
models were analyzed as four cases. The hot air mass
flow rates were kept at 1240 kg/h in all cases, and the
cooling air velocity was adjusted from 4 m/s to 10 m/s.
The standard k- turbulence model with shear
flow corrections was used to deal with high-speed
turbulent flow problems. The second-order upwind
difference scheme was adopted for the momentum,
energy and turbulence equations. The turbulence kinetic energy, k and its dissipation rate, , were obtained
from the following transport equations:
( k ) ( kui )

t
xi

k
t

k x j

Gk ,
x j

(1)

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x j

( ) ( ui )

t
xi
x j

t C k 2 / .
(2)

k =1.0, and =1.3.

where and are the density and viscosity, respectively, and t is the transport time. Gk represents the
generation of turbulence kinetic energy due to the
mean velocity gradients, calculated by

In Eqs. (1), (2) and (4), C1 , C2 , C , k , and

are constants: C1 =1.44, C2 =1.92, C =0.09,

C1 Gk k C2 2 k ,

u u
ui i j
x
j xi
Gk t /
x j

(4)

(3)

The k and are coupled to the governing equations via the relation:

(a)

The empirical constant for the turbulence model

was assigned values in accordance with the recommendation of Launder and Spalding (1972).
To deduce the porous media parameters, the
empirical correlation given by regressing experimental data to a certain function was adopted (Dong
et al., 2007b).
The calculation equations for wavy-fin are
written as (Dong, 2007b)
f 1.16 Re

0.309

Fp

Fh

0.3703

Fp

b

0.25

Ld
L

0.1152

, (5)

where Fp is the fin space, Fh is the fin height, L is the

wavelength, Ld is the entire flow length, and b is the
amplitude.
The calculation equations for a plane-fin are
written as
f 3.479 Re

0.389

Ld

Dc

0.396

Fh

Dc

0.113

Dc

0.21

, (6)

where is the fin thickness, and Dc is the hydrodynamic diameter of the fin.
According to the definition of friction factor f:

(b)

(c)

Fig. 1 3D model, grids and photo of the CAC and radiator

(a) CAC; (b) Radiator; (c) 3D model for simulations

f D (P Pi Pe )2 Vc2 Ld .

(7)

P 2 Vc2 Ld f / D Pi Pe ,

(8)

Then,

where Vc is the average velocity of the flow field, and

D is the hydrodynamic diameter of the fin. Pi and
Pe are the pressure differentials produced by the
circulation area abruptly narrowing and widening,
respectively. They are negligible in this case. We
calculated the factor f with different velocities, then
the pressure drop was derived. The porosity parameters were estimated from the correlation between the
velocity and pressure differential.

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CFD program Fluent 13 was used to solve these

problems in a super-computer with eight Intel Xeon
CPUs (2.0 GHz per CPU). It took about 20 h per case
for calculation with six CPUs involved.
2.2 Experiments

2.2.1 Test bench

A wind tunnel test platform (Fig. 2) consisting of
an cooling air system, water circulation system
(Fig. 3), hot air circulation system (Fig. 4), and experimental data acquisition system (Huang, 2010)
was constructed to test the heat exchangers.
In this platform, the main function of the cooling
air system was to emulate the actual flow in the running vehicle. It was controlled by adjusting fan speeds
to a maximum of 30 000 m3/h. Rectifying units, including honeycomb and gauze elements, were designed to make the flow uniform.
The heated air circulation system was used to
supply the hot air with adjustable temperature, flow
rate, and pressure. In this study, heated air substituted
for charged air. The hot air volume flow rate could be
adjusted from 4 m3/min to 50 m3/min, and the temperature range was from ambient to 300 C.
Like the heated air circulation system, the water
circulation system was adopted to emulate the cooling
water in an engine system, with adjustable temperature, flow rate, and pressure. The amount of water
flowing could be adjusted from 1 m3/h to 15 m3/h.
The water tank was open style, giving a permissible
temperature range from ambient to 99 C.
2.2.2 Test services and sensors
A Coriolis mass flow meter with a range from
0 kg/min to 600 kg/min was employed to measure the
hot air and water flow rate. Its error was 0.15%. A
ToCeil-FB thermal mass flow meter (Shanghai, China)
was used to measure the cooling air flow rate for the
merits of high sensitivity and stability. As for the
pressure, a few sensors were applied in different positions (Table 1).
The temperature data in this experiment was
monitored with Pt100 thermal resistors. All the temperature sensors were demarcated by a thermostatic
oil bath, and accuracy reached super A class. To
achieve reliable results, two temperature-measuring
nets (Fig. 5) composed of many sensors were set in
front of and behind the radiator, respectively.

Outflow
1 2 3

5 6 7 8 9

10

Inflow

11

Fig. 2 Sketch of the wind tunnel test system

1: air inlet section; 2, 9: honeycomb; 3: front stable section; 4, 8:
temperature-measuring net; 5, 7: pressure measurement; 6:
cooling modules (including CAC and radiator); 10: back stable
section and velocity measurement; 11: fan and outlet
1

M 2

8 9
P T

10

V4

14

13

P 11
T 12

Fig. 3 Sketch of the water circulation system

1: water tank; 2: agitation system; 3: cooling water; 4: electric
heater; 5: pumps; 6, 13: flow valve; 7: Coriolis mass flow
meter; 8, 11: pressure sensor; 9, 12: temperature sensor; 10:
radiator; 14: drainpipe

4
V

6 7
P T

9 10 11
T P

Inlet

Outlet

Fig. 4 Sketch of the hot air circulation system

1: air compressor; 2: air tank; 3: Coriolis mass flow meter; 4:
electric heater; 5, 11: flow valve; 6, 10: pressure sensor; 7, 9:
temperature sensor; 8: CAC

After the services were installed and organized,

we ran the test bench under the initial conditions. The
data were recorded while the system reached thermal
equilibrium.
2.3 Collaborated study method

To explore the interaction of adjacent modules,

combinations involving three different adjustments
were compared in this study: (1) Changing the relative positions; (2) Changing the spacing; and, (3)
Changing the flow pattern of the hot medium in the
CAC.
Firstly, we adjusted the relative position with
two methods: (A) Moving the CAC up, to align the
cores at the top; (B) Moving the CAC down, to align
the cores at the bottom.

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Table 1 Parameters of the pressure and differential pressure transducer

Measured parameter
Wind tunnel inlet pressure
Cooling air pressure
Cooling air pressure drop
Hot air inlet pressure
Hot air pressure drop
Water pressure
Water pressure drop

Sensor
Flow totalizer
Differential pressure transmitter
Differential pressure transmitter
Pressure sensor
Differential pressure transmitter
Pressure sensor
Differential pressure transmitter

Range (kPa)
0300
20
02.5
0300
0100
0600
0200

Precision (%)
0.50
0.25
0.25
0.25
0.25
0.25
0.25

Fig. 6 Photo of the CAC (model F)

(a)

3 Results
3.1 Numerical results analysis
(b)

(c)

Fig. 5 Photo of the experimental services

(a) Wind tunnel; (b) Temperature-measuring net between the
CAC and radiator; (c) Temperature-measuring net behind the
radiator

Then, to analyze the influence of module space,

two models were modified as follows, with all the
other structures kept the same: (C) Increasing the
modules space by 50 mm; (D) Increasing the modules space by 100 mm.
Finally, the effects of the flow pattern of the prior
module were analyzed in detail. The inlet and outlet
positions were changed as follows, with all the other
structures kept the same: (E) Turning the entire CAC
upside-down, with the hot air flowing from the lower
left corner to the lower right corner; (F) Turning the
right tank of the CAC upside-down, with hot air
flowing from the upper left corner to the lower right
corner (Fig. 6).
The tests and simulations were carried out according to these six methods, and the heat dissipations
(calculated by the measured temperature difference)
were contrasted and analyzed.

A few typical cross-sections of the original

model are extracted to demonstrate the internal flow
and temperature distribution. Fig. 7a shows the middle section in the CAC, Fig. 7b the parallel section
behind the CAC, and Fig. 7c the middle section in the
radiator. Clearly, the flow and temperature status of
the downstream module are highly reliant on the
status of the prior module. The mass flux across the
upper channels of the CAC is larger, therefore the
cooling air of the upper region is heated at a higher
temperature. In the present model, the heat dissipation
in the radiator was strongly influenced by the size and
position of the adjacent CAC tanks. This suggests that
collaborative analysis should be taken into account in
the design of cooling packages.
The velocity and temperature curves along the
X-minus direction inside and downstream of the radiator are illustrated in Fig. 8. The velocity distribution was nearly zygomorphic. In Fig. 8a, the upper
points indicate the velocity distributions in air channels, and the lower points indicate the velocity in
water-tubes. The air flow rates on the left and right
sides were relatively low owing to the block of CAC
tanks. The temperature distributions were exactly
contrary in Fig. 8b, in that the higher temperatures

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Velocity magnitude (m/s)

Fig. 7 Velocity and temperature distributions

(a) Middle section in the CAC; (b) Parallel section behind the CAC; (c) Middle section in the radiator
18
16 (a)
14
12
10
8
6
4
2
0
-290

-189

-86

16
X (mm)

119

222

Temperature (K)

360

3.2 Results validation

355
350
345
340

came from water-tubes and the lower values from the

air temperatures. At the intermediary region of the
core, both temperatures were higher on the left and
lower on the right. The lowest water temperature
appeared in the tube with the lowest water flow rate.
On the left and right sides, low flow rates of air incurred high temperatures, with the temperature values
of air and water being very close.

(b)

335
-290

-189

-86
16
X (mm)

119

222

Fig. 8 Velocity curve (a) and temperature curve (b) along

the X-minus direction in the middle of the radiator

To validate the numerical simulations, the computational results were compared to the test results
(Figs. 9 and 10). The computational and test results
display similar trends. When the cooling air flow rate
was increased, the pressure drop increased too, accompanied by an enhancement of heat exchange. Thus,
the temperature differences of hot air and water were
both enlarged.

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1400

50

P (Pa)

P (Pa)

30
20
Test

10
0

Test

1200

40

Case

1000
800
600
400

Simulation

(a)
1

Simulation

200
0

(b)
1

Case

90
80
70
60
50
40
30
20
10
0

T (K)

T (K)

Fig. 9 Comparison of the cooling air in tests and simulations

(a) Temperature difference; (b) Pressure drop

Test

Simulation

(a)
1

Case

9
8
7
6
5
4
3
2
1
0

Test

Case

Simulation

(b)
4

Fig. 10 Comparison of the temperature difference between tests and simulations

(a) Temperature difference of hot air; (b) Temperature difference of water

From these comparisons we found that the simulated temperatures deviated from the test results
more than did the flow resistances. This is probably
because: (1) the porous parameters were converted
from the empirical equations of the friction factor,
thus inaccuracies in anticipating heat exchange could
not be corrected; (2) the porous model in FLUENT 13
may not be accurate in processing the energy equation,
thereby giving poor results. However, in general, the
simulated and measured results matched well in their
trends. The data error was acceptable and could be
corrected by parameters. Thus, the simulation model
could be effectively used in further studies.
3.3 Collaborative analysis

The effects of changing the relative positions

were studied first. The heat dissipations in different
models (calculated by the measured temperature differences) are contrasted in Fig. 11, where model O
represents the original structure, and models A and B
represent the two adjusted structures.
Based on the field synergy principle proposed by
Guo and Huang (2004), the more uniform the temperature difference (between cold and hot mediums)
distribution, the better is the heat transfer performance.
A parameter, , defined as the uniformity factor of the
temperature difference field (TDF), was adopted to
describe the uniformity degree. In the cross flow heat
exchanger, it could be written as shown in Eq. (9):
2

Here, Cr=Cmin/Cmax is the heat capacity rate ratio,

and NTU is the number of heat transfer units.
Fig. 12 plots the parameter inside the radiator,
and Fig. 13 displays the TDF (between water and
cooling air) of the radiator mounted in modules. In
Fig. 13b, temperature differences are mainly in the
range of 25 to 50 C, less variable than the range of 20
to 55 C in Figs. 13a and 13c. At the same time, the
high temperature difference area marked by red (in
the web version) in Fig. 13b is obviously bigger than
those in Figs. 13a and 13c. More synergy and a larger
area of strong heat transfer indicate a better
performance.
Compared to the original structure and method B,
method A was slightly better at heat dissipation from
the radiator. The temperature of a radiator is generally
higher at the top and lower at the bottom. Although
the topside cooling air is heated by the CAC in method A, the temperature of the cold medium also appeared to be higher at the top and lower at the bottom.
This makes the TDF of the radiator more uniform
than the one in model B and in the original model, and
therefore the heat-transfer efficiency is higher accordingly. In terms of the prior module, the CAC,
there is no obvious relationship between the original
model and model B. However, it could be observed
that the change involved in model A is disadvantageous to the CAC.

1 exp{[1 exp( C r NTU)] / C r }

NTU{1 exp( C r NTU) {1 exp{[1 exp( C r NTU)] / C r }}}

(9)

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0.995
0.27

1.2
1.1

0.25

1.0

0.23

0.9

Radiator (model O)
Radiator (model A)
Radiator (model B)
CAC (model O)
CAC (model A)
CAC (Model B)

0.8
0.7
1

Case

0.21
0.19
0.17
0.15

Fig. 11 Heat dissipations of the water and hot air in

different positions
(a)

Y (mm)

X (mm)

Y (mm)

(b)

X (mm)

Y
(mm)
Y/mm

(c)

X (mm)

Fig. 13 TDF of the radiator mounted in module

(a) Model O; (b) Model A; (c) Model B

0.990
0.985

1.3

0.6

Model O
Model A
Model B

0.29
Qhot air (x105 J/s)

Qwater (x105 J/s)

1.4

0.980
0.975
0.970

7
8
v (m/s)

10

11

Fig. 12 Uniformity factor of the TDF in the radiator

The effects of changing the spacing were studied.

By carrying out experiments under the same conditions, we found that heat dissipations of both modules
were unaffected by changed spacing. Thus, we believe that spacing variation within a certain range
would not influence the heat-transfer efficiency.
Finally, simulations and experiments on different CAC structures were carried out. The adjusted
models were established and simulated in the same
way as the original model. In the original CAC, the
hot air inlet and outlet were both assigned to the top.
Most flow occurs across the upper channels. The
temperatures and flow rates of all channels were distinctly non-uniform. With the changing of the air-tank
structure, the flow patterns were transformed, and the
flow and temperature fields of the entire model were
changed accordingly. The velocity and temperature
distributions in the new models are shown in Fig. 14.
The flow patterns were clearly influenced by the tank
structure in the CAC. In model F, the flow path was
broadly lengthened and more channels were involved
in the mass-transfer. This represents more uniformity
in the allocation of hot medium, and makes better use
of the cooling air. From the temperature distribution
in the section behind the CAC, the cooling air of
model F is heated in a larger area compared to those
of model E and the original model (Fig. 7).
To validate the influence on the flow pattern,
wind tunnel measurements were carried out under
similar conditions. As plotted in Fig. 15, the curves
illustrate the heat dissipations calculated by the
measured temperature differences of hot mediums,
where model O means the original structure, and
models E and F represent the two modified structures.
Based on this figure, the heat dissipation of the
CAC in model F is visibly higher than those of model
E and the original model. As for the heat dissipation

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of the radiator in the three models, the data were very

similar, but the value in model F was always the
lowest. Comparing the hot-side pressure drop of the
CAC (Fig. 16), we found that the flow resistance
inside model F was about 12% higher than the resistance inside model E. However, with increasing
cooling air velocity, the hot-side pressure drop decreased gradually, and the mass flow rates remained
the same. This may be related to the variation in the
hot air properties. The increased cooling air flow rate
induces a better cooling effect. Accompanied by the
larger scope of the temperature drop, the density increases and the viscosity reduces, thus the flow resistance of the hot air declines accordingly. In light of
these results, the heat dissipation of one single module can be effectively improved by restructuring, but
with a penalty of higher resistance. The influence on

the thermal status of the next module was much less

than expected. Although the heat transfer of the CAC
was significantly enhanced, there was no substantial
influence on the performance of the radiator. This
indirectly reflects the fact that the intensity of heat
transfer depends not only on the average temperature
difference between the cold and hot mediums, but
also on the temperature distribution.

4 Conclusions

This study deals with a collaborative analysis of

adjacent heat exchanger modules in an automobile.
Numerical simulations and experiments were carried
out, and the results were very similar. Three kinds
of combination were selected to analyze the

Fig. 14 Velocity distribution of the middle section in the CAC and the temperature distribution inside and
behind the CAC
(a) Model E; (b) Model F

1.2

15

0.27

14

0.25

1.1

0.23

1.0
Radiator (model O)
Radiator (model E)
Radiator (model F)
CAC (model O)
CAC (model E)
CAC (model F)

0.9
0.8
0.7
0.6

0.29

Case

0.21
0.19

Phot arir (K)

Qwater (x105 J/s)

1.3

Qhot air (x105 J/s)

1.4

Model F

13
12
11
10

0.17

0.15

Fig. 15 Heat dissipations of the water and hot air in

different CAC structures

Model E

Case

Fig. 16 Hot-side pressure drop of the CAC

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interaction of adjacent modules and we found that the

heat dissipation of the modules is affected by their
relative position, and the rules comply with the field
synergy principle: the more uniform the temperature
difference (between cold and hot mediums) distribution, the better is the heat transfer performance.
Based on this study, the variation of spacing
within a certain range would not obviously influence
the heat-transfer efficiency. The heat exchange capacity of one single module can be effectively improved by restructuring, but with a penalty of higher
resistance. However, although the heat transfer of the
prior module was significantly enhanced, there was
no substantial influence on the performance of the
next module. This reflects the fact that the intensity of
heat transfer depends not only on the average temperature difference between cold and hot mediums,
but also on the temperature distribution.
Nevertheless, the interaction of adjacent heat
exchangers should not be neglected in limited spaces,
and deserves further investigation. This research
could provide a valuable reference for the design and
optimization of vehicular cooling systems.

Acknowledgements

Special material and technical support given for

this work by the Zhejiang Yinlun Company, China are
gratefully acknowledged.
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