Estimating the State of Health for Lithium-ion Batteries: A Particle Swarm Optimization-Assisted Deep Domain Adaptation Approach

doi:10.1109/JAS.2023.123531

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	Estimating the State of Health for Lithium-ion Batteries: A Particle Swarm Optimization-Assisted Deep Domain Adaptation Approach
	Guijun Ma; Zidong Wang; Weibo Liu; Jingzhong Fang; Yong Zhang; Han Ding; Ye Yuan
刊名	IEEE/CAA Journal of Automatica Sinica
	2023
卷号	10 期号:7 页码:1530-1543
关键词	Deep transfer learning domain adaptation hyperparameter selection lithium-ion batteries (LIBs) particle swarm optimization state of health estimation (SOH)
ISSN号	2329-9266
DOI	10.1109/JAS.2023.123531
英文摘要	The state of health (SOH) is a critical factor in evaluating the performance of the lithium-ion batteries (LIBs). Due to various end-user behaviors, the LIBs exhibit different degradation modes, which makes it challenging to estimate the SOHs in a personalized way. In this article, we present a novel particle swarm optimization-assisted deep domain adaptation (PSO-DDA) method to estimate the SOH of LIBs in a personalized manner, where a new domain adaptation strategy is put forward to reduce cross-domain distribution discrepancy. The standard PSO algorithm is exploited to automatically adjust the chosen hyperparameters of developed DDA-based method. The proposed PSO-DDA method is validated by extensive experiments on two LIB datasets with different battery chemistry materials, ambient temperatures and charge-discharge configurations. Experimental results indicate that the proposed PSO-DDA method surpasses the convolutional neural network-based method and the standard DDA-based method. The PyTorch implementation of the proposed PSO-DDA method is available at https://github.com/mxt0607/PSO-DDA.
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/51991]
专题	自动化研究所_学术期刊_IEEE/CAA Journal of Automatica Sinica
推荐引用方式 GB/T 7714	Guijun Ma,Zidong Wang,Weibo Liu,et al. Estimating the State of Health for Lithium-ion Batteries: A Particle Swarm Optimization-Assisted Deep Domain Adaptation Approach[J]. IEEE/CAA Journal of Automatica Sinica,2023,10(7):1530-1543.
APA	Guijun Ma.,Zidong Wang.,Weibo Liu.,Jingzhong Fang.,Yong Zhang.,...&Ye Yuan.(2023).Estimating the State of Health for Lithium-ion Batteries: A Particle Swarm Optimization-Assisted Deep Domain Adaptation Approach.IEEE/CAA Journal of Automatica Sinica,10(7),1530-1543.
MLA	Guijun Ma,et al."Estimating the State of Health for Lithium-ion Batteries: A Particle Swarm Optimization-Assisted Deep Domain Adaptation Approach".IEEE/CAA Journal of Automatica Sinica 10.7(2023):1530-1543.