Research on the Application of Reinforcement Learning in Hybrid Electric Vehicle Energy Management - ZHENG Chunhua; LI Wei (Journal of Harbin University of Science and Technology)
Aiming at the energy management of hybrid electric vehicles (HEVs), an energy management strategy based on the reinforcement learning (RL) is proposed. First, the HEV′s power system model and the Markov probability transfer model of the required power are established. Then, the RLbased control strategy is designed. Finally, it is compared with the dynamic programming (DP) algorithm and the rulebased energy management strategy. In UDDS, NEDC and Japan1015, the fuel economy of the RLbased strategy is 144%, 1022%, and 767% higher than that of the rulebased energy management strategy respectively. In addition, the fuel economy is over 92% of that of the DP algorithm on the three driving cycles, showing the effectiveness of the RLbased energy management strategy.