Optimal parameters estimation of the proton exchange membrane fuel cell stacks using a combined owl search algorithm

Abstract

PEMFC (the proton exchange membrane fuel cell) is an extremely effective energy converter system that generates electricity through electrochemical reactions. Optimizing the design of PEMFC stacks is important for their proper utilization and construction. In the current essay, we present a novel strategy for estimating optimal model parameters of proton exchange membrane fuel cell stacks utilizing the COSA (Combined Owl Search Algorithm), an improved metaheuristic algorithm. We compared the performance of COSA against other published methods, comprising COA, TLBO, BH, the original OSA, and BBO by employing them in three different cost functions. The results show that COSA achieved the minimum error values compared to the other algorithms for all case studies, with error values of 0.01, 1.20, and 0.93 for BCS 500W PEMFC, NedStackPS6, and SR-12 500 W PEMFC stack models, respectively. Our proposed approach could be utilized to optimize other kinds of fuel cells and integrated with other optimization strategies to improve its upcoming efficiency. Future work can focus on simplifying the algorithm structure to reduce its complexity during the optimization process. Overall, the COSA algorithm provides an effective tool for achieving more efficient and optimal fuel cell stacks.