Dynamic Semiempirical PEMFC Model for Prognostics and Fault Diagnosis

This article introduces a dynamic semiempirical model that predicts the degradation of proton exchange membrane fuel cell (PEMFC) by introducing time-based terms in model. The concentration voltage drop is calculated using new statistical equation based on load current and working time, whereas ohmic activation drops are updated equations borrowed from existing literature. Furthermore, developed calculates water content PEMFC, which indicates hydration state indirectly diagnoses flooding drying faults. Moreover, parameters optimized recently butterfly optimization algorithm. simple has short runtime; therefore, it suitable for monitoring. Voltage under various loading currents was observed long hours. obtained results indicate significant PEMFC performance. Therefore, proposed also useful prognostics fault diagnosis.