Research Description
Proton exchange membrane fuel cell (PEMFC) is considered as propitious solution for an environmentally friendly energy
source. A precise model of PEMFC for accurate identification of its polarization curve and in-depth understanding of all its
operating characteristics attracted the interest of many researchers. In this paper, novel meta-heuristic optimization
methods have been successfully applied to evaluate the unknown parameters of PEMFC models, particularly Harris
Hawks’ optimization (HHO) and atom search optimization (ASO) techniques. The proposed optimization algorithms have
been tested on three different commercial PEMFC stacks, namely BCS 500-W PEM, 500W SR-12PEM and 250W stack,
under various operating conditions. The sum of square errors (SSE) between the results obtained by the application of the
estimated parameters and the experimentally measured results of the fuel cell stacks was considered as the objective
function of the optimization problem. In order to validate the effectiveness of the proposed methods, the results are
compared with that obtained in studies. Moreover, the I/V curves obtained by the application of HHO and ASO showed a
clear matching with data sheet curves for all the studied cases. Finally, PEMFC model based on HHO technique surpasses
all compared algorithms in terms of the solution accuracy and the convergence speed.
