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

doi:10.32604/cmc.2020.011098

CASIA OpenIR > 中科院工业视觉智能装备工程实验室 > 工业智能技术与系统

	Lithium-Ion Battery Screening by K-Means with DBSCAN for Denoising
	Wang, Yudong1,2 ; Tan, Jie1 ; Liu, Zhenjie1 ; Ditta, Allah 3
发表期刊	CMC-COMPUTERS MATERIALS & CONTINUA
ISSN	1546-2218
	2020
卷号	65 期号:3 页码:2111-2122
通讯作者	Tan, Jie(tan.jie@tom.com)
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.
关键词	Lithium-ion battery battery screening K-means denoising
DOI	10.32604/cmc.2020.011098
关键词[WOS]	PACK
收录类别	SCI
语种	英语
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]
项目资助者	National Key Research and Development Program ; National Natural Science Foundation of China
WOS研究方向	Computer Science ; Materials Science
WOS类目	Computer Science, Information Systems ; Materials Science, Multidisciplinary
WOS记录号	WOS:000572868100015
出版者	TECH SCIENCE PRESS
七大方向——子方向分类	数据挖掘
引用统计	被引频次：4[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/41986
专题	中科院工业视觉智能装备工程实验室_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 Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 3.Univ Educ, Coll Rd Lahore Punjab, Lahore 54770, Pakistan
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
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.