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Lithium-Ion Cell Screening With Convolutional Neural Networks Based on Two-Step Time-Series Clustering and Hybrid Resampling for Imbalanced Data
Chengbao,Liu1,2; Jie, Tan1; Heyuan,Shi3; Xuelei,Wang1
Source PublicationIEEE ACCESS
2018-10
Issue6Pages:59001 - 59014
SubtypeResearch
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
Indexed BySCIE
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/23544
Collection综合信息系统研究中心
Corresponding AuthorJie, Tan
Affiliation1.Institute of Automation, Chinese Academy of Sciences
2.University of Chinese Academy of Sciences
3.School of Software, Tsinghua University
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Chengbao,Liu,Jie, Tan,Heyuan,Shi,et al. Lithium-Ion Cell Screening With Convolutional Neural Networks Based on Two-Step Time-Series Clustering and Hybrid Resampling for Imbalanced Data[J]. IEEE ACCESS,2018(6):59001 - 59014.
APA Chengbao,Liu,Jie, Tan,Heyuan,Shi,&Xuelei,Wang.(2018).Lithium-Ion Cell Screening With Convolutional Neural Networks Based on Two-Step Time-Series Clustering and Hybrid Resampling for Imbalanced Data.IEEE ACCESS(6),59001 - 59014.
MLA Chengbao,Liu,et al."Lithium-Ion Cell Screening With Convolutional Neural Networks Based on Two-Step Time-Series Clustering and Hybrid Resampling for Imbalanced Data".IEEE ACCESS .6(2018):59001 - 59014.
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