Optimal estimation of the Proton Exchange Membrane Fuel Cell model parameters based on extended version of Crow Search Algorithm

Abstract

This paper presents a new method for optimal model parameters estimation of the Proton Exchange Membrane Fuel Cell (PEMFC). The purpose is to find the optimal parameters such that the integral of the absolute error (IAE) between the output voltage of the real stack and the achieved data has been minimized. Different metaheuristics can be used for the minimization. Most of them have their shortcomings. Therefore, in this study, a new improved version of the Crow Search Algorithm (ICSA) is suggested to increase the algorithm diversity and to prevent trapping in the local minimum. The study has been then applied to two practical case studies, Nexa PEMFC and NedSstack PS6 PEMFC and the results are compared with some state of art methods, COA, (N + λ) - ES algorithm and basic CSA to show the better fitting of the suggested algorithm toward the others. The results show that IAE value for the Nexa PEMFC in ICSA, CSA, COA, and EA are 14, 16, 15, and 23, respectively and the IAE value for the NedStack PS6 PEMFC in ICSA, CSA, COA, and EA are 1.52, 1.76, 1.63, and 2.08, respectively that indicate the higher performance of the suggested algorithm when applying to both case studies.