Accurate parameters identification of proton exchange membrane fuel cell using Young’s double-slit experiment optimizer

Abstract

IntroductionFuel cell technology is a harbinger of the future for generating electricity due to their high efficiency and low emissions achieved through the direct conversion of chemical energy into electrical energy without combustion.MethodsTo optimize the design and performance, a fuel cell model is essential to predict its behaviour in different conditions. This technical note presents a novel physics-based approach, the Young’s Double-slit Experiment Optimizer (YDEO), for identifying parameters in Proton Exchange Membrane Fuel Cells. A performance metric is established by formulating an objective function that relies on the summation of squared errors between experimental and estimated values.Results and discussionThe effectiveness of this approach is evaluated through the analysis of four benchmark test cases: Horizon 500 W, BCS500 W, NedstackPS6, and 250 W. The corresponding objective function values for these test cases are 0.011243, 2.065557, 0.011698, and 5.250849, respectively. The simulation results demonstrate the efficacy of the proposed YDEO algorithm when compared with other existing popular and contemporary algorithms in the literature.