publication . Article . Other literature type . 2018

Energy Management Strategy for a Hybrid Electric Vehicle Based on Deep Reinforcement Learning

Yue Hu; Weimin Li; Kun Xu; Taimoor Zahid; Feiyan Qin; Chenming Li;
Open Access English
  • Published: 26 Jan 2018 Journal: Applied Sciences (issn: 2076-3417, Copyright policy)
  • Publisher: MDPI AG
Abstract
An energy management strategy (EMS) is important for hybrid electric vehicles (HEVs) since it plays a decisive role on the performance of the vehicle. However, the variation of future driving conditions deeply influences the effectiveness of the EMS. Most existing EMS methods simply follow predefined rules that are not adaptive to different driving conditions online. Therefore, it is useful that the EMS can learn from the environment or driving cycle. In this paper, a deep reinforcement learning (DRL)-based EMS is designed such that it can learn to select actions directly from the states without any prediction or predefined rules. Furthermore, a DRL-based online...
Subjects
ACM Computing Classification System: ComputerApplications_COMPUTERSINOTHERSYSTEMS
free text keywords: hybrid electric vehicle, energy management strategy, deep reinforcement learning, online learning, Technology, T, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999, MATLAB, computer.programming_language, computer, Driving cycle, Architecture, Energy management, Reinforcement learning, Electric vehicle, business.product_category, business, Control engineering, Engineering, business.industry
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Digital Humanities and Cultural Heritage
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publication . Article . Other literature type . 2018

Energy Management Strategy for a Hybrid Electric Vehicle Based on Deep Reinforcement Learning

Yue Hu; Weimin Li; Kun Xu; Taimoor Zahid; Feiyan Qin; Chenming Li;