A backtracking search algorithm combined with Burgerʹs chaotic map for parameter estimation of PEMFC electrochemical model

Polarization curves are vital tools for simulation, evaluation, management, and optimization of proton exchange membrane fuel cells (PEMFCs). They are affected by various parameters related to the nonlinearities associated with the electrochemical processes governing fuel cells (FCs). However, the relative importance and effect of each parameter on the polarization curve is different. In order to efficiently estimate the unknown parameters of the PEMFC electrochemical-based model and obtain accurate solutions, in this paper, a backtracking search algorithm combined with Burgerʹs chaotic map (BSABCM) is proposed and investigated. The results related to two real systems, the SR-12 Modular PEM Generator and the Ballard Mark V FC, illustrate the effectiveness of the proposed methodology. Furthermore, the BSABCM presented competitive results when compared with the results of the other metaheuristics.