FC degradation-aware optimal power allocation for FCEVs via nonlinear model predictive control

This study proposes a Nonlinear Model Predictive Control (NMPC) framework for optimal power allocation in Fuel Cell Electric Vehicle (FCEV) to optimize both fuel economy and the long-term durability of the fuel cell (FC) system. The objective function is designed to reconcile competing requirements: minimizing hydrogen consumption and maintaining the battery's state of charge while simultaneously mitigating degradation of the power sources. To specifically suppress catalyst degradation caused by extreme low-load operation, a sigmoid-based cost function is integrated into the NMPC. Driving simulations using a real-vehicle-based model demonstrated a 47% reduction in low-load operation time and a 29% decrease in FC power fluctuations. Furthermore, in FC degradation verification conducted with the physicochemical simulator FC-DynaMo, the proposed strategy achieved a 6.9% suppression of FC degradation while ensuring superior fuel efficiency.