An Efficient Parameter Estimation Algorithm for Proton Exchange Membrane Fuel Cells

The proton exchange membrane fuel cell (PEMFC) is a favorable renewable energy source to overcome environmental pollution and save electricity. However, the mathematical model of PEMFC contains some unknown parameters which have be accurately estimated build an accurate model; this problem known as parameter estimation belongs optimization problem. Although problem, not all algorithms are suitable solve it because nonlinear complex Therefore, in paper, new algorithm artificial gorilla troops optimizer (GTO), simulates collective intelligence nature, adapted for estimating GTO suffering from local optima low convergence speed problems, so modification based on replacing its exploitation operator with one, relating exploration according population diversity current iteration, has been performed improve addition one. This modified variant, named (MGTO), applied three stacks, 250 W stack, BCS-500W SR-12 used widely literature, minimizing error between measured data points objective function. outcomes obtained by applying MGTO those stacks extensively compared eight well-known using various performance analyses, best, average, worst, standard deviation (SD), CPU time, mean absolute percentage (MAPE), (MAE), Wilcoxon rank-sum test, show one best solving experimental findings that metrics, but time competitive among algorithms.