modeling the effective thermal conductivity of an

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1 Copyright © 2011 by ASME Proceedings of ASME 2011 5th International Conference on Energy Sustainability & 9th Fuel Cell Science, Engineering and Technology Conference ESFuelCell2011 August 7-10, 2011, Washington, DC, USA ESFuelCell2011-54364 MODELING THE EFFECTIVE THERMAL CONDUCTIVITY OF AN ANISOTROPIC GAS DIFFUSION LAYER IN A POLYMER ELECTROLYTE MEMBRANE FUEL CELL J. Yablecki University of Toronto Toronto, ON, Canada [email protected] A. Bazylak University of Toronto Toronto, ON, Canada [email protected] ABSTRACT The anisotropic and heterogeneous effective thermal conductivity of the gas diffusion layer (GDL) of the polymer electrolyte membrane fuel cell was determined in the through- plane direction using an analytical thermal resistance model. The geometry of the GDL was reconstructed using porosity profiles obtained through microscale computed tomography imaging of four commercially available GDL materials. The effective thermal conductivity increases almost linearly with increasing bipolar plate compaction pressure. The effective thermal conductivity was also seen to increase with increasing GDL thickness as bulk porosity remained almost constant. The effect of the heterogeneous through-plane porosity distribution on the effective thermal conductivity is discussed. The outcomes of this work will provide insight into the effect of heterogeneity and anisotropy of the GDL on the thermal management required for improved PEMFC performance. NOMENCLATURE A Area (m 2 ) a,b major and minor semi axes of elliptical contact area (m) C Contact point d Fiber diameter (m) E Young’s modulus (Pa) E’ effective elastic modulus (Pa) F Contact force (N) F 1 Integral function of ρ H Height of modeling domain (m) k Thermal conductivity (W/m K) K(η) Elliptical integral L Length of modeling domain (m) l Length of fiber (m) N Number of fibers P Pressure (Pa) q Heat flux (W/m 2 ) R Thermal Resistance (K / W) T Temperature (K) t Thickness of modeling domain layer (m) V Volume (m 3 ) W Width of modeling domain (m) Greek Symbols ε Porosity ρ’, ρ’’ Major and minor relative radii of curvature (m) ρ e Equivalent radius of curvature (m) θ Angle between two fibers (radians) υ Poisson’s ratio ξ Strain (m / m) Subscripts bp Bipolar plate C Contact point co Constriction resistance cond Conduction eff effective GDL Gas Diffusion Layer sp spreading resistance s solid fiber t thickness

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Page 1: MODELING THE EFFECTIVE THERMAL CONDUCTIVITY OF AN

1 Copyright © 2011 by ASME

Proceedings of ASME 2011 5th International Conference on Energy Sustainability & 9th Fuel Cell Science, Engineering and

Technology Conference

ESFuelCell2011

August 7-10, 2011, Washington, DC, USA

ESFuelCell2011-54364

MODELING THE EFFECTIVE THERMAL CONDUCTIVITY OF AN ANISOTROPIC

GAS DIFFUSION LAYER IN A POLYMER ELECTROLYTE MEMBRANE FUEL CELL

J. Yablecki University of Toronto

Toronto, ON, Canada

[email protected]

A. Bazylak University of Toronto

Toronto, ON, Canada

[email protected]

ABSTRACT

The anisotropic and heterogeneous effective thermal

conductivity of the gas diffusion layer (GDL) of the polymer

electrolyte membrane fuel cell was determined in the through-

plane direction using an analytical thermal resistance model.

The geometry of the GDL was reconstructed using porosity

profiles obtained through microscale computed tomography

imaging of four commercially available GDL materials. The

effective thermal conductivity increases almost linearly with

increasing bipolar plate compaction pressure. The effective

thermal conductivity was also seen to increase with increasing

GDL thickness as bulk porosity remained almost constant. The

effect of the heterogeneous through-plane porosity distribution

on the effective thermal conductivity is discussed. The

outcomes of this work will provide insight into the effect of

heterogeneity and anisotropy of the GDL on the thermal

management required for improved PEMFC performance.

NOMENCLATURE

A Area (m2)

a,b major and minor semi axes of elliptical contact area

(m)

C Contact point

d Fiber diameter (m)

E Young’s modulus (Pa)

E’ effective elastic modulus (Pa)

F Contact force (N)

F1 Integral function of ρ

H Height of modeling domain (m)

k Thermal conductivity (W/m K)

K(η) Elliptical integral

L Length of modeling domain (m)

l Length of fiber (m)

N Number of fibers

P Pressure (Pa)

q Heat flux (W/m2)

R Thermal Resistance (K / W)

T Temperature (K)

t Thickness of modeling domain layer (m)

V Volume (m3)

W Width of modeling domain (m)

Greek Symbols

ε Porosity

ρ’, ρ’’ Major and minor relative radii of curvature (m)

ρe Equivalent radius of curvature (m)

θ Angle between two fibers (radians)

υ Poisson’s ratio

ξ Strain (m / m)

Subscripts

bp Bipolar plate

C Contact point

co Constriction resistance

cond Conduction

eff effective

GDL Gas Diffusion Layer

sp spreading resistance

s solid fiber

t thickness

Page 2: MODELING THE EFFECTIVE THERMAL CONDUCTIVITY OF AN

2 Copyright © 2011 by ASME

INTRODUCTION

Achieving proper heat management within a polymer

electrolyte membrane (PEM) fuel cell is critical for improving

its performance and lifetime. Heat produced from the

electrochemical reaction and water phase change results in

temperature gradients across a single cell and fuel cell stack (1-

5). The temperature within the fuel cell affects the relative

humidity, membrane water content, saturation pressure, and

reaction kinetics. Careful control of the temperature throughout

the cell is also important to avoid membrane dehydration and

degradation at elevated temperatures and detrimental humidity

levels (4). Modeling the heat transfer rates and temperature

distributions in a fuel cell requires the knowledge of the

thermal transport properties, in particular, the effective thermal

conductivity.

The main path for heat removal from the PEM fuel cell

membrane to the current collectors is through the gas diffusion

layer (GDL), and the rate of heat removal is therefore largely

dependent upon the thermal transport properties of the GDL.

Although a number of analytical correlations exist for the

effective thermal conductivity of a composite material with

different geometric considerations (6), the GDL thermal

conductivity can be estimated but not accurately represented by

a single analytical correlation due to its anisotropic (7) and

heterogeneous nature (8). Through a compact analytical model

of the GDL, Sadeghi et al. (9) calculated the through-plane

effective thermal conductivity of the GDL using an idealized

repeating unit cell to represent the GDL structure. The

analytical model accounted for: the conduction through the

solid fibrous material, gas phase, the thermal constriction

resistance at the regions of fiber-to-fiber contact, and gas

rarefaction in the microgaps to determine the effective thermal

conductivity. The results from their model (9) and parametric

study showed that the thermal constriction resistance dominates

the total thermal resistance in the determination of the effective

thermal conductivity.

The work of Sadeghi et al. (9) was extended by the same

authors to include an experimental and analytical study on the

effective thermal conductivity and thermal contact resistance of

the GDL under a compressive load (10). Increases in the

bipolar plate pressure were found to increase the thermal

conductivity. Further to this approach, Sadeghi et al. (11)

recently published an experimental and analytical study on the

in-plane effective thermal conductivity and thermal contact

resistance of the GDL. The compact analytical model

accounted for heat conduction through randomly oriented

fibers, the contact area between fibers, and

polytetrafluoroethylene (PTFE) covered regions. Their work

(11) was the first combined analytical and experimental

approach to determining the in-plane thermal conductivity of

the GDL.

Recently, Pfrang et al. (12), Zamel et al. (13), and Veyret

et al. (14) used a commercial simulation software package

(GeoDict) to determine the anisotropic thermal conductivity of

the GDL. Pfrang et al. (12) calculated the effective thermal

conductivity of three commercially available GDLs with

GeoDict based on three-dimensional (3-D) reconstructions

from x-ray computed tomography (CT) visualizations. Zamel

et al. (13) used GeoDict to construct a 3-D pore morphology of

dry carbon paper GDL with no PTFE by providing the GDL

geometric parameters as the initial conditions. The thermal

conductivity was determined using two different commercial

solvers: ThermoDict and Fluent. Both programs yielded the

same results for the effective thermal conductivity, but

ThermoDict was found to have significantly less computational

requirements than Fluent.

The effective thermal conductivity of the GDL can be

determined experimentally in-situ from the temperature of an

operating fuel cell or from ex-situ experiments. Ex-situ

experiments for the GDL are more common due to the

complexity of coupled processes within an operating fuel cell,

which must be considered for in-situ measurements (15). The

first experimentally determined GDL thermal conductivity was

reported by Vie and Kjelstrup in 2003 (16). Burheim et al. (15)

reported experimental measurements for the anisotropic

through-plane effective thermal conductivity of dry and wet

Nafion membranes and compressed GDLs from ex-situ

experiments. Compression was shown to cause a nearly linear

increase on the effective thermal conductivity with applied

compression load. The thermal conductivity of the GDLs with a

residual water content of 25% was found to increase by almost

70% when compared with a dry sample. Burheim et al. (17)

recently reported an extensive study on the effective through-

plane thermal conductivity of a number of GDL materials. The

authors (17) studied the effect of residual water, PTFE content,

and compression on the through-plane thermal conductivity and

the thermal contact resistance between the GDL and aluminum

bi-polar plate.

Sadeghi et al. (9) provided insight into the through-plane

thermal conductivity of the GDL with a compact analytical

model but only considered the case of a periodic ordered GDL

structure. In practice, the GDL is anisotropic and carbon paper

GDL materials are composed of randomly oriented fibers.

Recent work by Fishman et al. (8) indicates that the porosity of

the GDL is heterogeneous. Burheim et al. (17) have attributed

experimentally found trends in the through-plane thermal

conductivity with the GDL thickness of carbon paper GDL

materials to this heterogeneity. It is important to investigate the

effect of heterogeneous porosity distributions on the effective

through-plane thermal conductivity of the GDL in more detail.

In this work, an analytical model is used to determine the

effective through-plane thermal conductivity of four

commercially available GDL materials based on the

heterogeneous porosity profiles presented in (8). The effects of

the heterogeneous porosity distribution and GDL compression

on the effective thermal conductivity are investigated. The

results of the model are compared with experimental data

presented in (17).

Page 3: MODELING THE EFFECTIVE THERMAL CONDUCTIVITY OF AN

3 Copyright © 2011 by ASME

MODEL DEVLEOPMENT

GDL Reconstruction To model the effective through-plane thermal conductivity

of the GDL, a modeling domain, shown in Figure 1, with width,

W, and length, L, was constructed of a number of randomly

oriented fibers, Nt, in the xy plane. The fibers are immersed in

stagnant air, each with a length and diameter of l and d,

respectively. Layers of the fibers are stacked vertically through

the entire thickness or height, H, of the GDL modeling domain.

The through-plane porosity distributions reported in (8) of

four GDL materials are employed in this work to establish the

number of fibers, in each layer, t, of the modeling domain. The

porosity of each layer can be found from:

�� � 1 � ��������� �1�

where Vsolid is the total volume of the solid carbon fibers, and

Vtotal is the total volume of modeling domain. Based on the

volumes of the modeling domain used, the porosity is

determined from:

�� � 1 � �� ���4 ���� �2�

where d and l are the diameter and length of the carbon fiber,

respectively.

In previous analytical modeling work, Sadeghi et al. (9)

found that the primary path for through-plane heat conduction

in the GDL is through the contact area formed by two fibers

overlapping with an orientation angle, θ.

Based on the assumption that both fibers are smooth, a

smooth, non-conforming contact area between the two fibers is

formed, which is a function of the force applied and the angle

between the two fibers. When cylindrical fibers contact each

other eccentrically, the contact region is close to elliptical (18).

The Hertzian theory of contact is used to predict the shape of

contact between solids and how it grows under an increasing

load (18). Following the analytical modeling approach for the

GDL presented by Sadeghi et al. (9), the application of the

Hertzian contact theory for non-conforming smooth cylinders is

used to define the contact area as (18):

� � ��"�′3 �!4"′ #

$/& $�3�

' � � (�′�")�/&

�4�

where a and b are the major and minor semi-axies of the

elliptical contact region, respectively, and F is the contact load.

Figure 1: Schematic illustrating a section of the geometry in the

computational domain, which consists of solid, continuous fibres

oriented in a planar direction a) x-y plane orientation, b) x-z plane

orientation, and c) isometric view.

The major and minor relative radii of curvature at the contact

points, ρ' and ρ'’ are given as (18):

�** � �+2�1�,-.2/ 0 2�5�

�* � 124�3 � 2 1�**3

�6�

E’ is a function of the Young’s modulus, E and Poisson’s ratio,

υ (18):

"* � (1 � 5$�"$ 0 1 � 5��"� )�7�

where the subscripts, 1 and 2, are used to denote the two

materials in contact. For this model the contact area is formed

between two fibers of the same material. ρe is the equivalent

radius of curvature expressed as (18):

�! � +�*�**�8�

Page 4: MODELING THE EFFECTIVE THERMAL CONDUCTIVITY OF AN

4 Copyright © 2011 by ASME

Sadeghi et al. (9) proposed the following relationship, accurate

within 0.8% for the complex integral function of ρ' and ρ'’, F1:

$ � 19.1√;1 0 16.76√; 0 1.34;�9�

where:

; � �*�** �10�

In our model, the number of contact points, Ct, for a single

fiber in layer, t, and the adjacent layer, t+1, is a function of the

porosity of both layers and the orientation angle of the fiber.

The fibers are randomly oriented with a uniform distribution in

the modeling domain with an angle between 0 and 90 degrees.

The maximum number of contact points for a given fiber in

each layer occurs when the fibre orientation angle is 90°, as

shown in the periodically ordered fiber arrangement (Figure 2).

The minimum number of contact points is seen when θ is 0°

between the two layers. A non-linear relationship was

determined for the number of contact points for a single fiber in

a layer with porosity εt based on its orientation angle. The

average number of contact points for a single fiber, Ct in a layer

with porosity εt was determined from this relationship and is

used as an input into the model. The average number of contact

points was assumed to vary linearly with porosity and is

interpolated for each porosity value, εt. The contact load, F, for each contact point can be

expressed in terms of the pressure within the GDL, PGDL, the

cross-sectional area of the unit cell defined by L and W, and the

number of contact points for a given layer, Ct (9):

=�>,� � @ABC��D� �11�

The pressure within the GDL will affect the uncompressed

values for the GDL thickness measured in (8). The strain, ξ,

from the GDL compression is assumed to be elastic and is

found from Hooke’s law:

E � "ABC@ABC �12�

where EGDL is the Young’s modulus of the GDL material.

Thermal Model

The effective thermal conductivity is a property of porous

media that accounts for the contributions of the thermal

conductivity of each phase (19). For determination of the

effective thermal conductivity of the GDL, the two phases that

are generally considered are carbon fibers and air with values

of thermal conductivity of 120 W/m K and 0.03 W/m K,

respectively (7). Results from analytical modeling work by

Sadeghi et al. (9) revealed that the dominant path for heat flow

Figure 2: Schematic illustrating a periodically ordered fiber

arrangement with θ = 90°

in the GDL is through fiber-to-fiber contact, and heat flow

through the air can be neglected. This was validated in

experimental work (10), where the calculated through-plane

thermal conductivity of the GDL in vacuum and ambient

conditions resulted in thermal conductivity values that differed

by less than 3%.

For the analytical model, it is assumed that the only heat

transfer is steady-state one-dimensional (1-D) conduction in the

through-plane direction of the GDL. With the calculation of the

Grashof and Peclet numbers, Ramousse et al. (7) showed that

natural convection and convective heat transfer are negligible

compared with conduction in the GDL. Radiative heat transfer

can be neglected for temperatures below 1000 K (20), which is

well above the operating range of a PEM fuel cell. Heat is

transferred through the modeling domain from fiber-to-fiber

contact only. The thermal resistance in the conduction along a

fiber is ignored as it is assumed to be negligible compared with

the thermal constriction and spreading resistances (10).

A thermal resistance network or circuit can be constructed

for 1-D heat transfer with no internal energy generation and

constant properties (21). The thermal resistance, Rt, for

conduction in a plane wall is defined by:

F�G�H� � ∆JK � �

LM�13�

where ∆T is the difference in temperature across the wall, q is

the heat flux, L is the length of the plane wall, k is the thermal

conductivity of the wall, and A is the cross sectional area of the

wall. An equivalent thermal circuit with thermal resistances in

parallel and series is analogous to an electrical circuit governed

by Ohm’s law.

The dominant thermal resistance for heat conduction

through the GDL is the thermal constriction and spreading

resistance (9). The thermal spreading resistance, Rsp, is

equivalent to the thermal constriction resistance, Rco, and

accounts for the thermal energy that is transferred between the

two fibers at the contact interface (9). When the dimensions of

the contact area are very small compared with the dimensions

of the contacting bodies, the heat transfer through the contact

Page 5: MODELING THE EFFECTIVE THERMAL CONDUCTIVITY OF AN

5 Copyright © 2011 by ASME

area is constrained, and the solution can be modeled as a heat

source on a half-space (22). In the case of the GDL, the contact

area between the two fibers is the heat source, and the much

larger carbon fibers are the half space.

The thermal constriction resistance is then a function of

the elliptical contact area calculated with the Hertizan contact

theory and described by the major and minor semi-axis of the

elliptical contact area, a and b, respectively. Using the work of

Yovanovich and Marotta (23) that resulted in half-space

solutions for different contact interfaces, Sadeghi et al. (9)

expressed the thermal constriction resistance analytically to be:

FG� � 12�L�' N�O��14�

where K(η) is the complete elliptical integral and a function of

the contact area dimensions, a and b.

N�O� = P ��+Q1 − O�.RS��T

U/�

V�15�

where:

O = W1 − 2� 'X 3��16�

The total thermal resistance for each layer, Rt, within the

modeling domain can be found from the summation of each

individual thermal resistance of each contact point in parallel:

1F� =Y 1

FG�,Z + F�[,Z\

V�17�

The total resistance in the modeling domain, Rtotal, can be found

as a series summation of the thermal resistances of each layer:

F���� =YF� �18��]^

V

The effective thermal conductivity can be found from the total

thermal resistance:

L!__ = �����F����M =` − �

F�������19�

RESULTS

The analytical model was implemented with

heterogeneous through-plane porosity distributions for Toray

carbon paper TGP-H-030, 060, 090, and 120 obtained through

x-ray microscale computed tomography (µCT) experiments

conducted in (8). The GDL materials considered were

uncompressed and did not have a microporous layer (MPL) or

PTFE treatment. The spatial resolution for the µCT data

Table 1: Unit Cell Geometry Properties

Fiber

diameter, d

Fiber

length, l

Unit cell

width, W

Unit cell

length, L

7.32 µm 325 µm 1500 µm 1625 µm

Table 2: Carbon Fiber Properties

Thermal

Conductivity, k

Poisson’s

ratio, υ

Young’s

Modulus, E

120 W/m K (3) 0.3 (13) 210 GPa (13)

gathered is 2.44µm (8); however, for the purpose of this model,

measurements for porosity are interpolated from the

experimentally determined data set at every 7.32 µm through

the thickness of the GDL. The details of the microscale

computed tomography visualization are presented in reference

(8). The geometric parameters of the modeling domain and the

material properties used in the analytical model are shown in

Tables 1 and 2. A value of 17.9 MPa for the Young’s modulus

of the Toray carbon paper GDL is used (24).

The effective through-plane thermal conductivity obtained

from the analytical model is shown in Table 3 for three

different compression pressures, Pbp. The results from the

analytical model are also plotted in Figure 3 and compared with

experimental data for Toray carbon paper GDL materials

presented by Burheim et al. (17). The results from the

analytical model are in agreement within 11.1%, 8.9%, and

3.1% of the experimentally obtained results from (17) for Toray

TGP-H-060, 090, 120, respectively. Similar trends can be seen

between both sets of data.

The effective thermal conductivity is observed to increase

with increasing compression pressure. As noted by Burheim et

al. (15), and shown in Figure 3, the effective thermal

conductivity increases almost linearly with increasing

compression pressure. The results from the analytical model

also display another trend noted in the experimental work by

Burheim et al. (17) for Toray carbon GDL material with

varying thickness. The results in Figure 3 show an increase in

the effective thermal conductivity with increasing GDL

thickness, even as the average bulk porosity remains

approximately consistent. This is the trend for all three GDL

materials presented by Burheim et al. (17). The results

presented in Figure 3 for the analytical model follow this trend

except for Toray TGP-H-060 and 090. The effective thermal

conductivity of Toray TGP-H-060 is an average of 3% higher

than 090. To investigate this trend further, the effective thermal

conductivity for each GDL material is plotted throughout the

thickness of the GDL in Figure 4.

Page 6: MODELING THE EFFECTIVE THERMAL CONDUCTIVITY OF AN

6 Copyright © 2011 by ASME

Table 3: Effective thermal conductivity of Toray paper GDLs

Toray TGP-H-030

Compression

Pressure

(kPa)

Thickness

(µm)

Bulk

Average

Porosity

(%)

Effective thermal

conductivity

(W/m K)

460 114.11

0.2601

930 111.03 82.93 0.3327

1390 108.02

0.3811

Toray TGP-H-060

460 213.96

0.4822

930 208.18 82.09 0.6038

1390 202.54

0.6722

Toray TGP-H-090

460 290.03

0.4678

930 282.2 82.60 0.5758

1390 274.55

0.6664

Toray TGP-H-120

460 349.46

0.6450

930 340.03 78.69 0.8180

1390 330.81

0.9292

As shown in Figure 4, the thermal conductivity through

the thickness of the GDL is strongly dependent upon the local

value of the porosity, εt. For all four GDL materials presented,

the Toray carbon paper materials display local porosity minima

and maxima throughout the thickness (8). At the location of a

porosity minimum, a maximum local value of thermal

conductivity is observed. The four materials investigated have a

local maximum value of thermal conductivity between 2.5 and

3 W/m K.

DISCUSSION

The effective thermal conductivity is observed to increase

with increasing compression pressure. This result has been

previously shown in experimental (9, 15, 17, 25) and analytical

work (9, 10) and can be explained with the analytical model

presented. As the compression pressure increases, the elliptical

contact area between two fibers increases. Increases in the

contact area cause a decrease in the thermal constriction and

spreading resistance, and subsequently, an increase in the

overall thermal conductivity. Compression will also cause a

decrease in the overall thickness of the GDL material that has

been accounted for in this analytical model. As the thickness of

the GDL decreases, the overall effective thermal conductivity

will also decrease. The effect of the compression on the

Figure 3: Comparison of measured average effective thermal

conductivity with compression pressure and with values from

Burheim et al. (17).

decrease in the thermal resistance is greater than the effect on

the decrease in the GDL thickness, therefore, causing an overall

increase in the effective thermal conductivity with increasing

compression.

The analytical model assumes that compression is applied

uniformly within the GDL. This is not the case during fuel cell

operation as there will be higher compression in areas under the

lands of the bipolar plate than in areas under the channels (15).

The Toray carbon paper materials display local porosity

minima and maxima throughout the thickness that affect the

local thermal conductivity value and the overall effective

thermal conductivity. Fishman et al. (8) noted that the

heterogeneous porosity distributions for all four GDL materials

are distinct but each display three different segments: two

transitional surface regions and a core region. The transitional

surface region extends linearly between the outer surfaces and

the local porosity minima and the core area is between the two

transitional surface regions (8). For the thinnest GDL

investigated, Toray TGP-H-030, this transitional surface region

accounts for approximately 66% of its total thickness (8).

Fishman et al. (8) observed that the transitional surface region

accounts for 45%, 33%, and 28% of the material thickness for

060, 090, and 120, respectively. The variation of the overall

effective thermal conductivity with GDL thickness observed in

Table 3 can be attributed to the amount of transitional surface

region. The thermal conductivity appears to be strongly

affected by the higher porosity values in the transitional surface

regions, regardless of the overall bulk porosity value or the

local maximum thermal conductivity value.

The results from the analytical model for the effective

thermal conductivity observe an increase in effective thermal

conductivity with increasing GDL thickness, same results

Page 7: MODELING THE EFFECTIVE THERMAL CONDUCTIVITY OF AN

7 Copyright © 2011 by ASME

presented by Pharaoh et al. discrepancy in analytical model for

Toray 060 and 090. The discrepancy between our analytical

results and the experimental results from literature stems from

the small variability in our experimentally obtained porosity

profiles of commercially available materials. Batch-specific

variations associated with the manufacturing process have been

observed in these commercially available materials (26). In this

work, only one sample for each different material was

employed as an input in our analytical model. Here, we see that

the results from the analytical model are quite sensitive to the

porosity values in the transitional regions, or locations of

porosity maximums. Future work should include a larger

number of porosity distributions in order to fully characterize

the trends on the effective thermal conductivity.

CONCLUSION

An analytical model to determine the effective thermal

conductivity of the GDL is presented. The model is used to

calculate the effective thermal conductivity of four

commercially available Toray carbon paper GDL materials

based on heterogeneous porosity profiles obtained from

microscale computed tomography imaging (8). The effect of

the heterogeneous porosity distribution and GDL compression

on the effective thermal conductivity is investigated. The

effective thermal conductivity increases almost linearly with

increasing bipolar plate compaction pressure. The effective

thermal conductivity was also seen to increase with increasing

GDL thickness as bulk porosity remained almost constant. The

effective thermal conductivity is affected by the heterogeneous

porosity distribution. The outcomes of this work will provide

insight into the effect of heterogeneity and anisotropy of the

GDL on the thermal management required for improved

PEMFC performance.

ACKNOWLEDGMENTS

The Natural Sciences and Engineering Research Council

of Canada (NSERC), Canada Foundation for Innovation (CFI),

Bullitt Foundation, and University of Toronto are gratefully

acknowledged for their financial support. Alexander Graham

Bell Graduate Scholarship from Natural Sciences and

Engineering Research Council of Canada (NSERC) is also

gratefully acknowledged.

REFERENCES

(1) N. Djilali, D. Lu. "Influence of heat transfer on gas and

water transport in fuel cells." Int. J. Therm. Sci., 2002:41 29-40.

(2) T. Berning, N Djilali. "A 3D, Multiphase, Multicomponent

Model of the Cathode and Anode of a PEM Fuel Cell." Journal

of The Electrochemical Society, 2003: 150 A1589-A1598.

(3) J. Ramousse, O. Lottin, S. Didierjean, D. Maillet. "Heat

Sources in proton exchange membrane (PEM) fuel cells."

Journal of Power Sources, 2009:192 435-441.

Figure 4. Through-plane effective thermal conductivity and

porosity distributions for Toray TGP-H- (a) 030, (b) 060, (c) 090

and, (d) 120.

a)

b)

d

c)

Page 8: MODELING THE EFFECTIVE THERMAL CONDUCTIVITY OF AN

8 Copyright © 2011 by ASME

(4) J.G. Pharoah, O.S. Burheim. "On the temperature

distribution in polymer electrolyte fuel cells." Journal of Power

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(5) T. Berning, D.M. Lu, and N. Djilali."Three-dimensional

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(6) M. Kaviany. Principles of Heat Transfer in Porous Media:

Second Edition. Springer: Mechanical Engineering Series,

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(7) J. Ramousse, S. Didierjean, O. Lottin, D. Maillet.

"Estimation of the effective thermal conductivity of carbon felts

used as PEMFC Gas Diffusion Layers." International Journal

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(8) Z.Fishman, J. Hinebaugh, A. Bazylak. "Microscale

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