Energy management of a fuel cell/ultracapacitor hybrid power system using an adaptive optimal-contro

Abstract Energy management of a fuel cell/ultracapacitor hybrid power system aims to optimize energy efficiency while satisfying the operational constraints. The current challenges include ensuring that the non-linear dynamics and energy management of a hybrid power system are consistent with state and input constraints imposed by operational limitations. This paper formulates the requirements for energy management of the hybrid power system as a constrained optimal-control problem, and then transforms the problem into an unconstrained form using the penalty-function method. Radial-basis-function networks are organized in an adaptive optimal-control algorithm to synthesize an optimal strategy for energy management. The obtained optimal strategy was verified in an electric vehicle powered by combining a fuel-cell system and an ultracapacitor bank. Driving-cycle tests were conducted to investigate the fuel consumption, fuel-cell peak power, and instantaneous rate of change in fuel-cell power. The results show that the energy efficiency of the electric vehicle is significantly improved relative to that without using the optimal strategy.