关键词: 插电式混合动力汽车；强化学习；Q-learning；能量管理策略

Abstract: Aiming at the energy management problem of plug-in hybrid electric vehicles, a strategy based on the Q-learning algorithm in reinforcement learning is proposed. Take battery state of charge and required power as state variables, take auxiliary power unit output power as control variable, and use Temporal-Difference Learning algorithm to update the action-state value in real time. Comparing the results with the global optimal algorithm pontryagin minimum principle, the total price of the Q-learning strategy is only 1.57 yuan more expensive under the Chinese type city bus circle of nearly 100 kilometers, which shows the effectiveness of the Q-learning strategy. From the perspective of application, this strategy is conducive to improving the overall economic level of vehicle.

Key words: Plug-in hybrid electric vehicles; Reinforcement learning; Q-learning; Energy management strategy