Modeling and optimization of a proton exchange membrane fuel cell using particle swarm algorithm with constriction coefficient

Abstract

The present study aims at estimating the values of an electrochemical model parameter of a proton exchange membrane fuel cell (PEMFC). A variant of the particle swarm optimization (PSO) algorithm is adopted. This variant introduces a constriction coefficient to better regulate the convergence of the numerical code. Parameters’ identification of the PEMFC stack model is performed by specifying a range for each. Validity of the adopted approach is confirmed by confronting simulation results with experimental data in terms of current–voltage polarization curves. It should be noted that the optimal value of the objective function is largely affected by the lower and upper values of the parameters. Comparison of present results with other optimization methods shows a noticeable improvement in PEMFC stack performance when using particle swarm optimization algorithm with constriction coefficient (PSO-χ). This confirms that this version of PSO algorithm is very suitable for the optimization and parameter estimation of PEMFC stack modeling.