PEM fuel cells: Two novel approaches for mathematical modeling and parameter estimation

Abstract

Proton Exchange Membrane Fuel Cells (PEMFCs) voltage-current characteristics are typically employed in PEMFC modeling and parameter estimation. The inverse current-voltage dependence is first reduced into one nonlinear equation in this study, examined, and then solved using two innovative iterative techniques. The proposed iterative processes’ accuracy has been examined in terms of the number of iterations necessary to reach a particular degree of accuracy.For both proposed iterative procedures, a high level of accuracy is achieved. Moreover, increasing the number of iterations increases the accuracy of calculations significantly. Second, a new hybrid variation of the Osprey optimization algorithm (OOA) and the Coati optimization algorithm (COA), two newly published optimization methods in the literature, is proposed for PEMFC parameter estimation. The sum of squares error (SSE) and root mean square error (RMSE) between measured and estimated PEMFC current are used as two objective functions. The comparisons indicate that the proposed algorithm outperforms the literature-known algorithms regarding convergence speed, accuracy, and statistical performance. The numerical findings from the parameter estimation testing for two different PEMFC cells validated the effectiveness of the proposed approaches for modeling and parameter estimation of the PEMFCs under investigation.