Multi-objective genetic optimization of the fuel cell hybrid vehicle supervisory system: Fuzzy logic and operating mode control strategies

A power train of the fuel cell vehicles includes the battery as a secondary power source to improve the vehicle's performance. In this composition, the vehicle's performance depends largely on quality of energy management strategies (EMSs). In this paper, two EMSs are introduced to control the energy in the fuel cell hybrid vehicle (FCHV). These are: fuzzy logic control (FLC) and operating mode control (OMC). Genetic algorithm (GA) is implemented to optimize these strategies by off-line simulation through a combined driving cycle. Comparison of these control methods with other approaches like EMS of advanced vehicle simulator (ADVISOR) software and non-optimized control strategies, demonstrate the superiority of optimized strategies regarding to equivalent energy consumption, energy efficiency, and state-of-charge (SOC) variation.