混合动力汽车工况识别与强化学习能量管理策略OA

With the rapid development of hybrid electric vehicles,optimizing energy management strategies has become crucial for enhancing vehicles' performance.To improve the adaptability of energy management strategies for plug-in hybrid electric vehicles,this paper employed clustering algorithms under standard driving conditions to extract four typical scenarios,building a scenario recognition model.It was then integrated with reinforcement learning to design an adaptive energy management strategy based on driving conditions.The weight factors of the reward function were adjusted according to different conditions.Next,a comprehensive energy management strategy that integrates scenario recognition and deep reinforcement learning was proposed.Through simulations and comparisons with dynamic programming and rule-based strategies,this approach achieved 94.29％in effectiveness compared to dynamic programming strategy while maintaining good adaptability under typical operating conditions for vehicles.This paper may provide some insights into real-time energy management for hybrid electric vehicles under multiple operational conditions.