A Novel Opposition-Based Arithmetic Optimization Algorithm for Parameter Extraction of PEM Fuel Cell

Abstract

The model-identification and parameter extraction are a well-defined method for modeling and development purposes of a proton exchange membrane fuel cell (PEMFC) to improve the performance. This paper introduces a novel opposition-based arithmetic optimization algorithm (OBAOA) for identifying the unspecified parameters of PEMFCs. The cost function is defined as the sum of the square deviations between the experimentally measured values and the optimal achieved values from the algorithm. Ballard Mark V PEM fuel cell is employed and analyzed to demonstrate the capability of the proposed algorithm. To demonstrate system efficiency, simulation results are compared to those of other optimizers under the same conditions. Furthermore, the proposed algorithm is validated through benchmark functions. The final results revealed that the proposed opposition-based arithmetic optimization algorithm can accurately retrieve the parameters of a PEMFC model.