Hierarchical control-based energy management strategy of intelligent battery/supercapacitor/fuel cell hybrid vehicles

In a complex traffic environment, dynamic changes bring difficulties in the safety of driving and optimizing energy management for fuel cell hybrid vehicles. Adding the supercapacitor (SC) may have advantages for energy distribution, which also challenges energy allocation problems. In response to these problems, a hierarchical control strategy for velocity optimization and energy management is proposed. Firstly, a safe distance adjustment mechanism is designed according to the road information and external disturbances considering the safe driving conditions. Secondly, the nonlinear model predictive control (NMPC) algorithm based on the sequence is adopted to obtain the optimal speed considering the ramp. Ultimately, an energy management strategy based on model predictive control (MPC) is designed to achieve a reasonable power allocation, which uses multi-objective performance functions to minimize the power source's degradation, extend the working life, and reduce energy consumption. At the same time, the influence of the supercapacitor on each performance index when it participates in energy supply is verified. The simulation results show that the designed strategies can obtain a safe optimal speed sequence and ensure safe driving with the preceding vehicle. Simultaneously, when the supercapacitor participates in the energy supply, the working life of the power sources is guaranteed, the hydrogen consumption in a long working condition is reduced by 28.51%, and the total cost is also reduced by 9.02%.