Parameter estimation of PEMFC model based on Harris Hawks' optimization and atom search optimization algorithms

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, theI/Vcurves 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.

Automated summary

Proton exchange membrane fuel cell (PEMFC) is considered a promising environmentally friendly energy source, and a precise model of PEMFC has been developed using novel meta-heuristic optimization methods. The proposed algorithms were tested on three different commercial PEMFC stacks and showed excellent solution accuracy and convergence speed. The results of the optimization methods compared favorably with previous studies and demonstrated clear alignment with data sheet curves.