Optimization Based Adaptive Cruise Control and Energy Management Strategy for Connected and Automated FCHEV

With the development of vehicle electrification, automation and connectivity, collaborative optimization among the traffic throughput, driving comfort, fuel economy and driving safety targets is still a huge challenging barrier for a connected and automated fuel cell/battery hybrid electric vehicle. Hence, this paper proposes an optimal car-following energy management strategy (EMS) that combines energy management and adaptive cruise control considering the above targets. Specifically, based on vehicle-to-vehicle and vehicle-to-infrastructure information, an optimal following distance algorithm is developed to obtain the optimal following distance considering driving safety, driving comfort and traffic throughput. Then, based on the established vehicle longitudinal dynamics model, an adaptive cruise controller using back-stepping technique is designed to accurately track optimal following distance. Meantime, combining the obtained controller, optimal EMS based on equivalent consumption minimization strategy is proposed to coordinate the output power of fuel cell and battery to improve fuel economy. The simulations of short and long-term driving cycles indicate that the proposed method can reduce hydrogen consumption by 12.12%, jerk by 61.21%, and keep the desired following distance tracking error within 0.5m.

Automated summary

This paper proposes an optimal car-following energy management strategy that combines energy management and adaptive cruise control to improve fuel economy of connected and automated fuel cell/battery hybrid electric vehicles.