Energy optimization for intelligent hybrid electric vehicles based on hybrid system approach in a car-following process

Considering the hybrid dynamical characteristics of multimode hybrid electric vehicle during a car-following process, a novel energy management strategy based on hybrid system theory is proposed in this article. Firstly, nonlinear powertrain model and longitudinal dynamics of a single-shaft parallel hybrid electric vehicle is built, and hybrid characteristics combined with continuous dynamics and discrete events during operating mode transition are described. Secondly, the nonlinear powertrain model and characteristics are approximated by the piecewise affine method, the mixed-logic dynamic modeling method is introduced and system variables are defined. Then the hybrid dynamical model for multimode hybrid electric vehicle in a car-following process is established with the hybrid system description language. Thirdly, according to the principle of receding horizon control, a hybrid model predictive controller is designed and applied for optimizing the multiobjective energy management problem in the car-following process. Finally, the proposed control strategy is compared with a rule-based control strategy, and the simulation results show that the proposed control strategy achieves fuel efficiency improvement while ensure the dynamic performance, driving safety and ride comfort during the car-following process, and the designed controller meets the requirement of deep fusion of car-following and energy management.