The powertrain configuration can significantly impact on the efficiency of the Fuel Cell Hybrid Electrical Vehicle (FCHEV), but most of the previous research pay more attention to the control strategy than the powertrain structure. In this study, a novel configuration of FCHEV which integrating dual Fuel Cell Stack (FCS) system and a Super Capacitor (SC) is proposed, then an optimal control strategy based on the fuzzy control is introduced to distribute the power requirement among the energy sources. Further the power distribution to the FCS is redistributed between the two FCSs through an minimum efficiency-based control strategy, which can extend the high efficiency region compared with only one FCS which leads to save hydrogen consumption. The proposed control strategy can distribute the lower frequency part of the power requirement to the fuel stack system and reduce the fluctuation of power supply, which leads to extend the life span of the fuel stack system. Through Advisor-Simulink and test bench experiment results, the proposed control strategy can effectively reduce the output power fluctuation of the FCSs within the range of 200 w/s, and save at least 6% the hydrogen consumption compared with the system with only one FCS.

Because of the soft dynamic performance of the fuel cell stack, the battery is usually integrated in the power system in fuel cell hybrid electric vehicles. In this paper, a real time energy management strategy considering thermal constraints based on speed prediction with neuron network is proposed. The main principle of the proposed control strategy is to get the future power requirement with model predictive control based on the historic speed information, and then optimize the objective function according to the state variables. The objective function is set to minimize the equivalent fuel consumption of the vehicle and extend the life span of the fuel cell stack based on thermal constraints. Contrasting with the control strategy without thermal constraints under the WLTC driving cycle, the proposed energy management is 0.9% higher, but the temperature of the fuel cell stack and the battery can be limited within an appropriate range. The total equivalent fuel consumption is 3.9% lower than dynamic programming control strategy, which proves the availability of the proposed control strategy can reduce the equivalent fuel consumption while prolonging the fuel cell stack life span. Hardware in loop (HIL) experiment is implemented to testify the real time application of the proposed control strategy.