Estimating the State of Health for Lithium-ion Batteries: A Particle Swarm Optimization-Assisted Deep Domain Adaptation Approach
文献类型:期刊论文
作者 | Guijun Ma; Zidong Wang; Weibo Liu; Jingzhong Fang; Yong Zhang![]() |
刊名 | IEEE/CAA Journal of Automatica Sinica
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出版日期 | 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. |
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. |
入库方式: OAI收割
来源:自动化研究所
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