Real-Time Energy Management based on the Prediction of Hybrid Vehicle's Future States

This paper proposes an optimal predictive energy management strategy for hybrid vehicle. The proposed strategy is designed according to a hierarchical control layers. The highest level (third) can predict battery state of charge; vehicle power consumption; Internal Combustion Engine (ICE) and Electrical Motor (EM) current optimal efficiencies. In the second level, an optimal controller is developed to generate the optimal EM and ICE torques set points. Then, in the first level, there are robust controllers to regulate the set points of each vehicle subsystems. A MATLAB/TruckMaker simulation results show that the proposed strategy increases vehicle energy efficiency w.r.t. other strategy.