The method of gain parameterizing measurement data and parameter estimation for a proton exchange membrane fuel cell model

Proton exchange membrane fuel cells (PEMFCs) are a technology that produces clean energy, with promising prospects in wide applications because of their high power density and low operating temperature. Experiments conducted to develop the PEMFC are both time-consuming and costly. Through modeling and simulation, performance development and analysis can be done more efficiently. This paper presents a simulation model for PEMFC based on mathematical equations developed using MATLAB/Simulink. To fully grasp and reproduce PEMFC characteristics, empirical parameter estimation using the genetic algorithm (GA) is implemented. The parameters estimated from the loss equations have not been previously utilized. A script connecting Simulink and the GA was developed to estimate these parameters. Validation is conducted by comparing the polarization curve simulation results with experimental data for both single-cell and stack-type PEMFCs. Comparisons with various other estimation methods were conducted to assess the reliability of the employed method. The model that utilizes estimated parameters exhibits agreement with experimental data showcasing an error value <3%. Furthermore, the method's superiority is evident from the polarization curve as well as the objective value. Observing the reaction conditions in each PEMFC loss region with the obtained parameter values becomes easier and more accessible.