Precise Parameter Extraction for Proton Exchange Fuel Cells by Mutated Quadratic Interpolation Algorithm

Abstract Precision modelling is required to design, control, and optimize proton exchange membrane fuel cells (PEMFCs). A PEMFC constitutes a nonlinear optimization problem defined by seven unknown variables and nonlinear equations. The research proposes combining the mutation phase of Differential Evolution (DE) with Quadratic Interpolation Optimization (QIO) to ascertain PEMFC parameters efficiently. Sum of squared errors (SSE) is suggested as an objective function, which calculated the error between the experimental measures and simulated voltage. The algorithm has been tested utilizing real data for four types of PEMFC: SR-12, Temasek 1 KW, BCS-500 W, and 250 W. The results show that the Mu-QIO have a superiority over the traditional QIO. To validate the superiority of the proposed algorithm, it is compared with the traditional QIO and well known algorithms.The robust correlation between the simulated and observed polarization curves corroborates the method's capacity to estimate unknown parameters. Furthermore, statistical performance metrics indicate the algorithm's consistent supremacy in all evaluated settings, highlighting its robustness and adaptability.