LAUSR

Proton‐exchange‐membrane fuel cells (PEMFCs) are a popular source of alternative energy because of their operational reliability and compactness. This paper presents an improved model to represent the semi‐empirical voltage of PEMFCs to overcome the limitations of existing models. The proposed model considers variations in ambient conditions, such as the ambient temperature and relative humidity, to obtain the accurate output voltage that corresponds to variations in dynamic and static loads. The proposed model was developed by conducting several experiments on the Horizon PEMFC system under normal, humid, and dry ambient conditions. Subsequently, the model parameters corresponding to each case were optimised using the quantum lightning search algorithm (QLSA). Parameters demonstrating significant variations with ambient conditions were finally represented as a function of the ambient temperature and relative humidity via statistical regression analysis. The voltage obtained using the modified model was verified by conducting experiments on both the Horizon and NEXA PEMFC systems by varying the ambient temperature and relative humidity with root mean square error (RMSE) less than 0.5. As observed, the results we obtained using the modified model closely approximated those obtained using PEMFCs under various operating conditions, and in both cases, the PEMFC voltage was observed to vary with the ambient and load conditions. The inherent advantages of the proposed PEMFC model include its ability to determine the membrane‐water content and water pressure inside PEMFCs. The membrane‐water content provides clear indications regarding the occurrence of drying and flooding faults. Under normal conditions, this membrane water content ranges from 11 to 7 for both the Horizon and NEXA PEMFC system. The simulation results suggested using the threshold membrane‐water‐content level as a possible indicator of fault occurrence under extreme ambient conditions. The limits of the said threshold were observed to be useful for fault diagnosis within PEMFC systems.