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Proton exchange membrane fuel cells (PEMFCs) have become a practical and promising alternative energy source for the automotive industry, offering high efficiency and zero-carbon emissions compared to internal combustion engines. Sustainable fuel cell (FC) operation in vehicles is dependent on effective water management. This study investigates impact of local, ambient relative humidity (RH) level variation on the water content and overall performance of a 5-kW open-cathode PEMFC. A Simcenter Amesim model of the FC was first developed, calibrated, and validated using experimental data. The model was tested under various scenarios to comprehensively analyze how changes in local RH affect membrane water content, reflected in the polarization curve, FC power, and ohmic losses. The results show that FC efficiency improves by 23%, while ohmic resistance drops from 0.72 Ω·cm² to 0.26 Ω·cm² as the local RH increases from 10% to 90%. 

Proton exchange membrane (PEM) fuel cells have emerged as a viable alternative energy production source for stationary and transportation applications. Reliable and sustainable fuel cell operation requires effective water management. Membrane water content can vary along the stack during transients which can lead to losses in fuel cell performance. To control these variations, a model that predicts the internal humidity dynamics of the stack is needed. In this study, a control-oriented model for predicting membrane water content variation was developed and implemented in MATLAB/Simulink. A lumped parameter model was initially developed and then further discretized into smaller control volumes to track humidity distribution along the stack. To validate the model’s predictions, the predicted results were compared to computer simulation results from GT-Suite. The root mean square error (RMSE) between the model’s prediction and GT-Suite’s simulation results was found to be within 1.5 membrane water content for all cases, demonstrating the model’s capability to capture the variation in membrane water content along the stack. The developed model will be useful for real-time control of membrane water content distribution in PEM fuel cells.