An accurate method for parameter estimation of proton exchange membrane fuel cell using Dandelion optimizer

Abstract

Abstract The Proton Exchange Membrane Fuel Cell (PEMFC) has found widespread use for regulated output voltage applications because of its quick response time and mobility. A different form of hydrogen is employed in fuel cell-based electric vehicles for smart transportation for the reduction of global warming and the development of smart cities. To properly manage the operation of Fuel Cells (FCs), there is a need for accurate modeling. One of the most common challenges is finding the exact values of unknown parameters in the PEMFC. In the current study, a new method called Dandelion Optimizer (DO) is used for parameter identification. DO is used to estimate the parameters of the PEMFC based on Current-Voltage (I-V) characteristics. The Ballard Mark V and BCS 500-W PEMFC stacks use the DO method to identify unknown parameters. The performance of the DO algorithm is compared to that of other optimization techniques and the Sum of Squared Errors (SSE) is used to represent the objective function of the current optimization problem. In contrast to traditional and other efficient techniques, the simulation results proposed by the DO algorithm have excellent accuracy in extracting the PEMFC optimal parameters.