Lithium-Ion Power Battery Grouping: A Multisource Data Fusion-Based Clustering Approach and Distributed Deployment

doi:10.1115/1.4053307

CORC > 自动化研究所 > 中国科学院自动化研究所 > 综合信息系统研究中心 > 工业智能技术与系统

	Lithium-Ion Power Battery Grouping: A Multisource Data Fusion-Based Clustering Approach and Distributed Deployment
	Wang, Yudong 1; Bai, Xiwei 2; Liu, Chengbao 2; Tan, Jie 2
刊名	JOURNAL OF ELECTROCHEMICAL ENERGY CONVERSION AND STORAGE
	2022-05-01
卷号	19 期号:2 页码:12
关键词	analysis and design of components devices and systems batteries electrochemical storage reliability
ISSN号	2381-6872
DOI	10.1115/1.4053307
通讯作者	Tan, Jie(tan.jie@tom.com)
英文摘要	Consistence of lithium-ion power battery significantly affects the life and safety of battery modules and packs. To improve the consistence, battery grouping is employed, assembling batteries with similar electrochemical characteristics to make up modules and packs. Therefore, grouping process boils down to unsupervised clustering problem. Current used grouping approaches include two aspects, static characteristics based and dynamic based. However, there are three problems. First, the common problem is under utilization of multi-source data. Second, for the static characteristics based, there is grouping failure over time. Third, for the dynamic characteristics based, there is high computational complexity. To solve these problems, we propose a distributed multisource data fusion based battery grouping approach. The proposed approach designs an effective network structure for multisource data fusing and feature extracting from both static and dynamic multisource data. We apply our approach on real battery modules and record state of health (SOH) during charging-discharging cycles. Experiments indicate that the proposed approach can increase SOH of modules by 3.89% and reduce the inconsistence by 68.4%. Meanwhile, with the distributed deployment the time cost is reduced by 87.9% than the centralized scheme.
资助项目	National Key R&D Program of China[2020YFB1710600] ; National Natural Science Foundation of China[U62003344] ; National Natural Science Foundation of China[U1701262] ; National Natural Science Foundation of China[U1801263]
WOS关键词	CONSISTENCY ; DESIGN ; CELLS
WOS研究方向	Electrochemistry ; Energy & Fuels
语种	英语
出版者	ASME
WOS记录号	WOS:000778139700013
资助机构	National Key R&D Program of China ; National Natural Science Foundation of China
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/48298]
专题	综合信息系统研究中心_工业智能技术与系统
通讯作者	Tan, Jie
作者单位	1.Chinese Acad Sci, Inst Automat, Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100190, Peoples R China 2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Wang, Yudong,Bai, Xiwei,Liu, Chengbao,et al. Lithium-Ion Power Battery Grouping: A Multisource Data Fusion-Based Clustering Approach and Distributed Deployment[J]. JOURNAL OF ELECTROCHEMICAL ENERGY CONVERSION AND STORAGE,2022,19(2):12.
APA	Wang, Yudong,Bai, Xiwei,Liu, Chengbao,&Tan, Jie.(2022).Lithium-Ion Power Battery Grouping: A Multisource Data Fusion-Based Clustering Approach and Distributed Deployment.JOURNAL OF ELECTROCHEMICAL ENERGY CONVERSION AND STORAGE,19(2),12.
MLA	Wang, Yudong,et al."Lithium-Ion Power Battery Grouping: A Multisource Data Fusion-Based Clustering Approach and Distributed Deployment".JOURNAL OF ELECTROCHEMICAL ENERGY CONVERSION AND STORAGE 19.2(2022):12.