Lithium-Ion Battery Screening by K-Means with DBSCAN for Denoising

doi:10.32604/cmc.2020.011098

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 Battery Screening by K-Means with DBSCAN for Denoising
	Wang, Yudong 1,3; Tan, Jie 1; Liu, Zhenjie 1; Ditta, Allah 2
刊名	CMC-COMPUTERS MATERIALS & CONTINUA
	2020
卷号	65 期号:3 页码:2111-2122
关键词	Lithium-ion battery battery screening K-means denoising
ISSN号	1546-2218
DOI	10.32604/cmc.2020.011098
通讯作者	Tan, Jie(tan.jie@tom.com)
英文摘要	Batteries are often packed together to meet voltage and capability needs. However, due to variations in raw materials, different ages of equipment, and manual operation, there is inconsistency between batteries, which leads to reduced available capacity, variability of resistance, and premature failure. Therefore, it is crucial to pack similar batteries together. The conventional approach to screening batteries is based on their capacity, voltage and internal resistance, which disregards how batteries perform during manufacturing. In the battery discharge process, real time discharge voltage curves (DVCs) are collected as a set of unlabeled time series, which reflect how the battery voltage changes. However, few studies have focused on DVC based battery screening. In this paper, we provide an effective approach for battery screening. First, we apply interpolation on DVCs and give a method to transform them into slope sequences. Then, we use density-based spatial clustering of applications with noise (DBSCAN) for denoising and treat the remaining data as input to the K-means algorithm for screening. Finally, we provide the experimental results and give our evaluation. It is proved that our method is effective.
资助项目	National Key Research and Development Program[2018YFB1703400] ; National Natural Science Foundation of China[U1801263] ; National Natural Science Foundation of China[U1701262]
WOS关键词	PACK
WOS研究方向	Computer Science ; Materials Science
语种	英语
出版者	TECH SCIENCE PRESS
WOS记录号	WOS:000572868100015
资助机构	National Key Research and Development Program ; National Natural Science Foundation of China
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/41985]
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, Beijing 100190, Peoples R China 2.Univ Educ, Coll Rd Lahore Punjab, Lahore 54770, Pakistan 3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Wang, Yudong,Tan, Jie,Liu, Zhenjie,et al. Lithium-Ion Battery Screening by K-Means with DBSCAN for Denoising[J]. CMC-COMPUTERS MATERIALS & CONTINUA,2020,65(3):2111-2122.
APA	Wang, Yudong,Tan, Jie,Liu, Zhenjie,&Ditta, Allah.(2020).Lithium-Ion Battery Screening by K-Means with DBSCAN for Denoising.CMC-COMPUTERS MATERIALS & CONTINUA,65(3),2111-2122.
MLA	Wang, Yudong,et al."Lithium-Ion Battery Screening by K-Means with DBSCAN for Denoising".CMC-COMPUTERS MATERIALS & CONTINUA 65.3(2020):2111-2122.