A Fitting Process for the Optimal Modelling of an Anion Exchange Membrane (AEM) Electrolyser

Empirical and semi-empirical numerical models of electrolysers and fuel cells are used to predict their behaviour and study rapidly how the performance of a technology changes. Both the polarisation and efficiency curves are mainly dependent on both pressure and temperature and, with a few experimental data, it is possible to forecast the cell behaviour at different operating conditions without performing any additional tests. However, numerical models do not always resemble the system’s performance properly due to the lack of information on crucial parameters like the kinetics ones; indeed, these parameters are difficult to retrieve from the scientific literature and the manufacturers of such technologies. Starting from a semi-empirical model of an Anion Exchange Membrane (AEM) electrolyser from the scientific literature, this paper aims to provide a methodology to assess these parameters with a fitting process. Results showed that the use of fitted coefficients led to a better prediction of the AEM electrolysers behaviour. The model showed a better fitting of the activation and Ohmic regions lowering the Root Mean Square Error (RMSE) by 3.5%, moving from 0.065 V in the original model to 0.03 V in the fitted one.