Temperature distribution, mass transport, and current density are crucial parameters to characterize the durability and output performance of proton exchange membrane fuel cell (PEMFC), which are affected by thermal contact resistance (TCR) and gas diffusion layer (GDL) face permeability within both cathode and anode GDL porous jumps. This study examined the effects of TCR and GDL face permeability on a single PEM fuel cell's temperature profiles, mass transport, and cell performance using a three-dimensional, nonisothermal computational model with an isotropic gas diffusion layer (GDL). This model calculates the ideal thermal contact resistance by comparing the expected plate-cathode electrode temperature difference to the numerical and experimental literature. The combined artificial neural network-genetic algorithm (ANN-GA) method is also applied to identify the optimum powers and their operating conditions in six cases. Theoretical findings demonstrate that TCR and suitable GDL face permeability must be considered to optimize the temperature distribution and cell efficiency. TCR and GDL face permeability lead to a 1.5 °C rise in maximum cell temperature at 0.4 V, with a "Λ" shape in temperature profiles. The TCR and GDL face permeability also significantly impacts electrode heat and mass transfer. Case 6 had 1.91, 6.58, and 8.72% higher velocity magnitudes, oxygen mass fractions, and cell performances than case 1, respectively. Besides, the combined ANN-GA method is suitable for predicting fuel cell performance and identifying operation parameters for optimum powers. Therefore, the findings can improve PEM fuel cell performance and give a reference for LT-PEMFC design.
© 2023 The Authors. Published by American Chemical Society.