An accurate parameter estimation of PEM fuel cell using war strategy optimization

The design, simulation, optimization, and assessment of Proton Exchange Membrane Fuel Cell (PEMFC) based real-time systems require an accurate model with appropriate parameters. This article presents a novel metaheuristic optimization technique, the War Strategy Optimization (WSO) algorithm, for estimating the fuel cell model parameters. The proposed WSO algorithm is inspired by ancient kingdoms’ combat techniques and tactics. During the war, the movements of the soldiers are pre-planned, and their positions are dynamically changed following a strategy. In the proposed algorithm, an algorithmic framework with a mathematical model is developed based on the war strategies. For the selection of optimal parameters, an objective function based on the sum of the square errors between measured and estimated voltage for distinct data points is formulated. The proposed WSO algorithm is applied to identify the parameters of three popular benchmark test suits. The statistical findings are compared to the various popular algorithms presented in the literature. The comparison of statistical values reveals that the proposed WSO algorithm is superior in terms of accuracy, search capability, and convergence speed.