关键词: 插电式混合动力汽车；能量管理；强化学习；转移概率矩阵

Abstract: The plug-in hybrid is energy efficient, and the energy management strategy among multiple power sources has a great impact on the energy consumption of hybrid vehicles. Taking a run on a fixed line series plug-in hybrid city bus as an example, based on the previous cycles, according to markov theory, the demand for power transformation along with the change of time for the state transition matrix, the random power sequence is generated by probability matrix. Module Q reinforcement learning and training, by using the random power sequence to realize the energy distribution of the city bus real-time optimization control. Simulation results show that the proposed reinforcement learning energy management algorithm can significantly optimize energy consumption compared with the rule control algorithm, and can greatly improve the time efficiency compared with dynamic programming and other global optimization strategies, and realize real-time control.

Key words: Plug-in hybrid electric vehicle; Energy management; Reinforcement learning; Transition probability matrix