Energy Management Strategy for Plug-in Hybrid Electric Bus with Evolutionary-Reinforcement Learning Method

doi:10.3901/JME.2017.16.086

Abstract

Abstract: A growing number of plug-in hybrid electric buses(PHEB) emerge in the city traffic field. In order to achieve better economical performance of PHEB, the study of energy management strategy(EMS) for PHEB is become the focus of the research. This paper proposes a method of EMS for PHEB based on reinforcement learning. First of all, a simplified vehicle model is presented, and the function of optimal energy consumption is obtained through the reinforcement learning system. Secondly, initial population of control strategy respect to the cost function, and optimal control strategy and energy consumption value are obtained using evolutional algorithm. Finally, simulation results are presented to illustrate the effectiveness of this method. The cost of the energy consumption via novel strategy in this paper decrease about 12% compared with traditional CDCS strategy.

Key words: energy management strategy, evolutionary algorithm, plug-in hybrid electric bus, reinforcement learning, single-shaft parallel

CLC Number:

U469

CHEN Zheng, LIU Yahui, YANG Fang. Energy Management Strategy for Plug-in Hybrid Electric Bus with Evolutionary-Reinforcement Learning Method[J]. Journal of Mechanical Engineering, 2017, 53(16): 86-93.

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