A novel approach to modeling of polymer electrolyte membrane fuel cells with vehicle-level validation in a hydrogen electric vehicle

This study presents a novel modeling approach for polymer electrolyte membrane fuel cells (PEMFCs), validated at both the single-cell and stack levels in a hydrogen electric vehicle. An extensive single-cell experiment was conducted to investigate the impacts of operating conditions (i.e., temperature, relative humidity, and pressure), leading to the development of a detailed PEMFC model incorporating newly derived water transport properties of a reinforced composite membrane (RCM). Unlike conventional models (CM) based on Nafion correlations, the RCM model successfully reproduced the distinct transport characteristics of the reinforced membrane. As a result, predictive accuracy was markedly enhanced, with the maximum root mean square error (RMSE) reduced from 41.0 mV (CM) to 6.3 mV (RCM). The model achieved an adjusted coefficient of determination (Radj2) of 0.988 and a maximum relative error below 2.01 %. Additionally, the model enabled analysis of through-plane distributions of temperature and water concentration (vapor and liquid), highlighting the saturation factor in the serpentine flow field configuration. At the stack level, chassis dynamometer tests under dynamic loads validated the model, with correction factors applied to account for flow channel differences. With these refinements, the stack model achieved an Radj2 of 0.994 and a maximum relative error below 3.15 %. This study bridges the gap between single-cell and stack-scale operation by integrating electrochemical and water transport effects into a scalable framework, providing a robust tool for predicting PEMFC performance under dynamic conditions.