Estimation of Effective Transport Properties for PEM Fuel Cells

Direct measurement of physical parameters for the polymer electrolyte membrane (PEM) fuel cells is always difficult due to the complex structure of fuel cell components and lack of technical advancement for in-situ measurement. For instance, the effective transport properties (effective conductivity and diffusivity) in the cathode catalyst layer of a PEM fuel cell play an import role to the overall electro-kinetic transport processes, and direct measurement of such properties is almost impossible. Conversely, the numerical modeling, which is considered a viable tool to predict the performance of PEM fuel cells, requires proper estimates of the effective properties for predicting the true nature of transport processes and hence, the performance of fuel cells. In the present study, a set of mathematical formulations is proposed for estimating the effective transport properties in both the catalyst and gas diffusion layers of a PEM fuel cell. The effective conductivity and diffusivity expressions are derived from the mathematical formulations of the Hashin Coated Sphere model, which provides an identical mathematical foundation for each of these effective properties. A wide range of comparison is also presented, which reveals the predictive capabilities of the proposed expressions. An excellent agreement between the proposed formulations and results available in literature further depicts that the proposed formulations can replace the widely used Bruggeman approximation for the effective transport properties in a PEM fuel cell, particularly in the numerical modeling. Further, the cumbersome combination of the Wiener model and Bruggeman approximation that is widely used in estimating effective diffusivity can be easily avoided using the proposed formulations. In addition, the Bruggeman approximation is purely based on empirical correlation, while the proposed formulations have its physical and mathematical origins; hence, the proposed formulations will provide consistent estimates compared to the empirical predictions.