CASIA OpenIR  > 综合信息系统研究中心
Lithium-Ion Cell Screening W th Convolutional Neural Networks Based on Two-Step Time-Series Clustering and Hybrid Resampling for Imbalanced Data
Liu, Chengbao1,2; Tan, Jie1; Shi, Heyuan3; Wang, Xuelei1
Source PublicationIEEE ACCESS
ISSN2169-3536
2018
Volume6Issue:Pages:59001-59014
Abstract

Due to the material variations of lithium-ion cells and fluctuations in their manufacturing precision, differences exist in electrochemical characteristics of cells, which inevitably lead to a reduction in the available capacity and premature failure of a battery pack with multiple cells configured in series, parallel, and series parallel. Screening cells that have similar electrochemical characteristics to overcome the inconsistency among cells in a battery pack is a challenging problem. This paper proposes an approach for lithium-ion cell screening using convolutional neural networks (CNNs) based on two-step time-series clustering (TTSC) and hybrid resampling for imbalanced data, which takes into account the dynamic characteristics of lithium-ion cells, thus ensuring that the screened cells have similar electrochemical characteristics. In this approach, we propose the TTSC to label the raw samples and propose the hybrid resampling method to solve the sample imbalance issue, thereby obtaining labeled and balanced datasets and establishing the CNN model for online cell screening. Finally, industrial applications verify the effectiveness of the proposed approach and the inconsistency rate of the screened cells drops by 91.08%.

KeywordLithium-ion cell screening time-series clustering resampling convolutional neural networks
DOI10.1109/ACCESS.2018.2875514
WOS KeywordOF-CHARGE ESTIMATION ; BATTERY PACKS ; ELECTRIC VEHICLES ; CLASSIFICATION ; MECHANISM ; DISCHARGE ; SMOTE ; LIFE
Indexed BySCI
Language英语
Funding ProjectNational Nature Science Foundation of China[U1701262] ; Intelligent Manufacturing New Model Application Project of the Ministry of Industry and Information Technology of the People's Republic of China[2016ZXFM06005]
WOS Research AreaComputer Science ; Engineering ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS IDWOS:000449646300001
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Cited Times:4[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/22582
Collection综合信息系统研究中心
Corresponding AuthorTan, Jie
Affiliation1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Tsinghua Univ, Sch Software, Beijing 100084, Peoples R China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Liu, Chengbao,Tan, Jie,Shi, Heyuan,et al. Lithium-Ion Cell Screening W th Convolutional Neural Networks Based on Two-Step Time-Series Clustering and Hybrid Resampling for Imbalanced Data[J]. IEEE ACCESS,2018,6(无):59001-59014.
APA Liu, Chengbao,Tan, Jie,Shi, Heyuan,&Wang, Xuelei.(2018).Lithium-Ion Cell Screening W th Convolutional Neural Networks Based on Two-Step Time-Series Clustering and Hybrid Resampling for Imbalanced Data.IEEE ACCESS,6(无),59001-59014.
MLA Liu, Chengbao,et al."Lithium-Ion Cell Screening W th Convolutional Neural Networks Based on Two-Step Time-Series Clustering and Hybrid Resampling for Imbalanced Data".IEEE ACCESS 6.无(2018):59001-59014.
Files in This Item: Download All
File Name/Size DocType Version Access License
Lithium-Ion Cell Scr(19745KB)期刊论文作者接受稿开放获取CC BY-NC-SAView Download
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Liu, Chengbao]'s Articles
[Tan, Jie]'s Articles
[Shi, Heyuan]'s Articles
Baidu academic
Similar articles in Baidu academic
[Liu, Chengbao]'s Articles
[Tan, Jie]'s Articles
[Shi, Heyuan]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Liu, Chengbao]'s Articles
[Tan, Jie]'s Articles
[Shi, Heyuan]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: Lithium-Ion Cell Screening With Convolutional Neural Networks Based on Two-Step Time-Series Clustering and Hybrid Resampling for Imbalanced Data.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.