Multi-optimization of thermodynamic performance of an HT-PEM fuel cell based on MOPSO algorithm

In this study, an irreversible thermodynamic model for the high temperature proton exchange membrane fuel cell taking electrochemical and heat losses into account is developed. The power density, exergy destruction index, exergy sustainability index and ecological coefficient of performance is derived. The model was validated against experimental data. The influence of parameters on the irreversible thermodynamic performance of high temperature proton exchange membrane fuel cell are considered. The multi-objective particle swarm optimization algorithm is utilized to optimize the power, ecological coefficient of performance and efficiency. The population distribution of the optimization variables was analyzed using a threedimensional Pareto frontier analysis, and results show that the maximum power density, maximum efficiency and maximum ecological coefficient of performance being 6340 W/m 2 , 64.5% and 1.723 respectively, which are 43.28%, 3.7% and 17.8% higher than the preoptimized high temperature proton exchange membrane fuel cell. Moreover, the nondominated sorting genetic algorithm II and simulated annealing algorithm have been chosen versus multi-objective particle swarm optimization algorithm for making the optimization comparative analysis.