A Two-Layer Real-Time Optimal Control for Intelligent Hybrid Electric Vehicles with Connectivity

Taking advantage of both vehicle-to-everything (V2X) communication and automated driving technology, connected and autonomous vehicles are rapidly becoming one of the transformative solutions to many traffic problems. However, during the car-following process how to solve the multi-objective optimization problem including safety, economy and comfort remains a challenging task. In this paper, a two-layer control strategy for intelligent hybrid electric vehicles with connectivity is proposed to solve this problem. In the upper layer, the vehicle speed is planned based on network information to improve vehicle comfort under the premise of ensuring safety. In the lower layer, based on the velocity trajectory obtained from the upper layer, the alternating direction method of multipliers (ADMM) algorithm is used to allocate the engine and motor torque to improve the fuel economy. Simulation results show that following safety can be guaranteed. And proposed energy management strategy (EMS) can obtain 6.96% fuel economy improvement compared with rule-based EMS under the China typical urban driving cycle.