Flow channel structure optimization and analysis of proton exchange membrane fuel cell based on the finite data mapping and multi-field synergy principle

Abstract

Design and optimization of the flow channel structure is an effective approach to improve the performance of the proton exchange membrane fuel cell (PEMFC). Based on the three-dimensional mathematical model of a single cell, this paper applied the artificial neural network method to obtain the exact relationship between the flow channel geometry size and the output performance of PEMFC with finite data by combining response surface analysis and central composite design. Under the Based on this model, the optimal double-inverted trapezoidal tapering channel structure and related dimensional parameters are obtained by NSGA-II algorithm. The comparisons show that the optimized PEMFC improves the peak power by 8.5% and extends the operating range of current density by 15.5%. Multi-field synergy principle analysis revealed a 5.95% increase in overall heat transfer capability, enhanced mass transfer capability on the cathode side, and a 28.57% increase in the average mass fraction of oxygen at the diffusion layer and runner crossover. In addition, the total drainage capacity was increased by 5.35%. In conclusion, the proposed finite data mapping optimization method and multi-field synergistic theoretical analysis can effectively guide and evaluate the design and optimization of the PEMFC.