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Fast Learning-based Control for Energy Management of Hybrid Electric Vehicles

机译:基于快速学习的混合动力汽车能源管理控制

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In this paper, a fast learning-based control method is proposed for energy management of hy-brid electric vehicles. First, the modeling of a parallel hybrid electric vehicle (HEV) is introduced. Energy management of the parallel HEV is constructed as an optimal control problem. Then, the reinforcement learning (RL) framework is depicted and a learning-based approach named Dyna-H algorithm is illustrated via incorporating a heuristic planning strategy into a Dyna agent. Finally, the proposed energy management strategy is compared with the benchmark methods to show its merits. Results indicate that the learning-based controls have better performance in fuel economy and calculation speed.
机译:本文提出了一种基于快速学习的混合动力汽车能源管理控制方法。首先,介绍了并联混合动力电动汽车(HEV)的建模。并联混合动力汽车的能量管理被构造为最佳控制问题。然后,描述了强化学习(RL)框架,并通过将启发式计划策略合并到Dyna代理中,说明了一种基于学习的方法Dyna-H算法。最后,将提出的能源管理策略与基准方法进行比较,以显示其优点。结果表明,基于学习的控件在燃油经济性和计算速度方面具有更好的性能。

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