Model Predictive Control with Adaptive Compensation for Power Management in Fuel Cell Hybrid Electric Vehicles

Fuel cell hybrid electric vehicles (FCHEVs) employing hydrogen fuel cells (FCs) as the main power source and supercapacitors (SCs) as the energy butter could be a feasible electrified transportation technology. This paper proposes a model predictive control scheme with adaptive compensation (ACMPC) for power management in FCHEV FC/SC hybrid energy storage systems. To address the concerns of linear model predictive control schemes with fixed weights, ACMPC introduces adaptive weights based on the SC state of charge (SOC) and compensates for the errors associated with the linearization of the nonlinear HESS. Simulation results show that by minimizing the SC SOC fluctuation, the FC current, and the FC current change rate, the load power is properly allocated to the FC and the SC, the hydrogen consumption is reduced, and the FC degradation is alleviated.