A novel approach for PEM fuel cell parameter estimation using LSHADE-EpSin optimization algorithm

Among the various fuel cell types, proton exchange membrane fuel cells (PEMFCs) have prominent characteristics that make them unique in applications. However, the preciseness of results of a PEMFC model depends on the availability of the parameters, which are missing in the datasheets provided by the manufacturers and vendors, and this explains why it becomes convenient to estimate such parameters for a complete and precise PEMFC model that closely matches the experimental measures under different operation conditions. In this work, a novel solution methodology based on applying an ensemble sinusoidal parameter adaptation incorporated with L-SHADE, called LSHADE-EpSin optimization algorithm, is proposed to solve the PEMFC parameter extraction problem. The proposed methodology is applied to four commercial PEMFCs: 250 W PEMFC; NedStack PS6, 6 kW; BCS 500 W; and SR-12500 W, and the results obtained are compared with the results obtained by using other recent optimization algorithms. Furthermore, several statistical tests were performed to validate the proposed model's performance and compare between the investigated algorithms. The results show the effectiveness of the approach proposed using the LSHADE-EpSin algorithm in estimating the optimal PEMFC parameters under different operating conditions compared to the other optimizers for the four studied stacks.