Reinforcement Learning Optimized Look-Ahead Energy Management of a Parallel Hybrid Electric Vehicle

doi:10.1109/TMECH.2017.2707338

	Reinforcement Learning Optimized Look-Ahead Energy Management of a Parallel Hybrid Electric Vehicle
	Liu, Teng 4; Hu, Xiaosong 2,5; Li, Shengbo Eben 3; Cao, Dongpu 1
刊名	IEEE-ASME TRANSACTIONS ON MECHATRONICS
	2017-08-01
卷号	22 期号:4 页码:1497-1507
关键词	Energy management hybrid electric vehicle (HEV) Markov chain (MC) predictive control reinforcement learning (RL)
ISSN号	1083-4435
DOI	10.1109/TMECH.2017.2707338
通讯作者	Liu, Teng(tengliu17@gmail.com) ; Hu, Xiaosong(xiaosonghu@ieee.org)
英文摘要	This paper presents a predictive energy management strategy for a parallel hybrid electric vehicle (HEV) based on velocity prediction and reinforcement learning (RL). The design procedure starts with modeling the parallel HEV as a systematic control-oriented model and defining a cost function. Fuzzy encoding and nearest neighbor approaches are proposed to achieve velocity prediction, and a finite-state Markov chain is exploited to learn transition probabilities of power demand. To determine the optimal control behaviors and power distribution between two energy sources, a novel RL-based energy management strategy is introduced. For comparison purposes, the two velocity prediction processes are examined by RL using the same realistic driving cycle. The look-ahead energy management strategy is contrasted with shortsighted and dynamic programming based counterparts, and further validated by hardware-in-the-loop test. The results demonstrate that the RL-optimized control is able to significantly reduce fuel consumption and computational time.
资助项目	EU - Marie SklodowskaCurie[706253-pPHEVH2020-MSCA-IF-2015]
WOS关键词	MODEL-PREDICTIVE CONTROL ; ECMS
WOS研究方向	Automation & Control Systems ; Engineering
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000408142300002
资助机构	EU - Marie SklodowskaCurie
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/28015]
专题	中国科学院自动化研究所
通讯作者	Liu, Teng; Hu, Xiaosong
作者单位	1.Cranfield Univ, Ctr Automot Engn, Bedford MK43 0AL, England 2.Chongqing Univ, Dept Automot Engn, Chongqing 400044, Peoples R China 3.Tsinghua Univ, Dept Automot Engn, State Key Lab Automot Safety & Energy, Beijing 100084, Peoples R China 4.Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Inst Automat, Beijing 100864, Peoples R China 5.Chongqing Univ, State Key Lab Mech Transmiss, Chongqing 400044, Peoples R China
推荐引用方式 GB/T 7714	Liu, Teng,Hu, Xiaosong,Li, Shengbo Eben,et al. Reinforcement Learning Optimized Look-Ahead Energy Management of a Parallel Hybrid Electric Vehicle[J]. IEEE-ASME TRANSACTIONS ON MECHATRONICS,2017,22(4):1497-1507.
APA	Liu, Teng,Hu, Xiaosong,Li, Shengbo Eben,&Cao, Dongpu.(2017).Reinforcement Learning Optimized Look-Ahead Energy Management of a Parallel Hybrid Electric Vehicle.IEEE-ASME TRANSACTIONS ON MECHATRONICS,22(4),1497-1507.
MLA	Liu, Teng,et al."Reinforcement Learning Optimized Look-Ahead Energy Management of a Parallel Hybrid Electric Vehicle".IEEE-ASME TRANSACTIONS ON MECHATRONICS 22.4(2017):1497-1507.