A new heuristic optimization algorithm for modeling of proton exchange membrane fuel cell: bird mating optimizer

As an open and demanding problem, accurate modeling of polarization curve in proton exchange membrane fuel cell has become the main issue of various researches. In recent years, because of their great potentials, metaheuristic optimization algorithms have represented good performances in identification of the unknown parameters of the proton exchange membrane fuel cell model, but there is the possibility to obtain more accurate results with more capable algorithms. In the literature, many heuristic optimization algorithms have been developed on the basis of natural phenomena. However, there are still some possibilities to devise new ones. In this paper, evolution of bird species has been regarded, and the intelligent behavior of birds during mating season has become an inspiration to devise a new heuristic optimization algorithm, named bird mating optimizer. Moreover, in this paper, the whole unknown parameters of the model, even dimensional parameters, are included in the identification process. The proposed algorithm is used to model the Ballard Mark V FC, and its performance is compared with those of the recently published paper by the authors. Simulation results reveal the superior performance of bird mating optimizer algorithm. Copyright (c) 2012 John Wiley & Sons, Ltd.