Numerical prediction of effective thermal conductivity of catalyst layers in proton exchange membrane fuel cells

The proton exchange membrane fuel cell (PEMFC) has attracted great attention due to its high efficiency, little pollution and low noise. Catalyst layer (CL) is one of the most crucial subassemblies in PEMFC. A deep understanding of transport processes inside the CL is of great importance for improving PEMFC performance. Due to its complex microscale structure and extremely thin thickness, there is still much work remaining for the prediction of effective thermal conductivity of CLs. Accurate prediction of the effective thermal conductivity of CL helps to improve the thermal and water management in PEMFC. Pore-scale numerical studies are performed in this study to investigate the heat transfer process in CLs. First, pore-scale structures of the CLs with multiple components are reconstructed. An aggregate shape control algorithm based on probability (ASCAP) is adopted, and then Pt particles and ionomer are distributed on the surface of carbon skeleton by quartet structure generation set (QSGS) method. Based on transmission electron microscope (TEM) measurement, the shape of reconstructed aggregate is selected as the largest proportional shape in the real structures. Then, the thermal lattice Boltzmann model is adopted to study heat transfer in the reconstructed structures and effective thermal conductivity is determined by the temperature field obtained. Effects of porosity, I/C ratio and size effects are investigated in detail. It is found that size effect must be considered for accurate prediction. The numerical results are proved to agree well with existing results from experiments and empirical solutions in the literatures.