Accurate Proton Exchange Membrane Fuel Cell Modelling Using Hiking Optimizer

Proton Exchange Membrane (PEM) Fuel Cells represent a promising clean energy technology due to their high efficiency and low environmental impact. However, accurate modeling of PEM fuel cells is critical for their optimization and integration into energy systems. Traditional models often suffer from inaccuracies due to suboptimal parameter selection. This research addresses the need for a precise PEM fuel cell model by introducing an innovative parameter optimization technique. The Hiking Optimizer (HO), a novel algorithm inspired by the dynamic and adaptive strategies used in hiking, is employed to optimize the parameters of a mathematical model for PEM fuel cells. The HO algorithm's ability to navigate complex search spaces effectively makes it particularly suited for this task. The proposed optimization approach is evaluated through two benchmark case studies and its performance is compared with three well-established algorithms. The experimental results demonstrate that the Hiking Optimizer not only improves the accuracy of the PEM fuel cell model but also achieves superior optimization performance compared to the other algorithms.