Three-dimensional electrochemical performance prediction of polymer electrolyte fuel cell cathodes using an anisotropic sub-grid scale lattice Boltzmann model

A three-dimensional numerical model is developed to predict the electrochemical performance of polymer electrolyte fuel cell cathodes using catalyst-layer microstructures reconstructed from focused ion beam scanning electron microscopy images. Proton conduction, gas diffusion, and electrochemical reactions are solved using the lattice Boltzmann method (LBM). To reduce the computational cost while retaining local microstructural information, an anisotropic sub-grid scale (SGS) model is introduced. In this model, direction-dependent effective diffusivities and conductivities are evaluated from the reconstructed microstructures and assigned to each coarse computational cell, allowing the coarse-grid simulation to retain the local anisotropic transport characteristics of the catalyst layer. The model is validated under various operating conditions. The calculated cathode overpotentials agree well with the experimental results, with errors of less than 8%. The overpotential breakdown also shows physically reasonable trends. The validated model is then applied to cathodes with different ionomer distributions. The results show that increasing the ionomer content near the membrane side improves cathode performance. This trend is further confirmed by experiments using double-layer cathode electrodes. The proposed framework provides a practical method for connecting microstructural information with cathode performance prediction, which can support future catalyst layer design.