Multi-objective optimization of PEMFC performance based on grey correlation analysis and response surface method

This paper aims to combine grey correlation analysis and response surface method propose a fast effective performance optimization for PEMFC. First, based on orthogonal test data, is used select four variables that have significant influence PEMFC’s comprehensive from eight common parameters. Secondly, analysis, the multi-objective problem transformed into single objective about degree, applying build key parameters between second order prediction model. Therefore, current density, system efficiency oxygen distribution uniformity cathode catalyst layer of PEMFC were optimized as whole. Finally, optimal parameter combination was obtained by optimizing The simulation results show operating conditions are significantly improved in three indexes compared with basic model, which confirms feasibility this solving problem, can provide some reference design hydrogen fuel cells.