A New Health Assessment Approach of Lithium-Ion Batteries Under Variable Operation Conditions

Sheng Hong; Yining Zeng

doi:10.1007/978-3-030-62460-6_17

A New Health Assessment Approach of Lithium-Ion Batteries Under Variable Operation Conditions

Sheng Hong^*
, Yining Zeng

^*此作品的通讯作者

网络空间安全学院

Nanchang University

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

摘要

The monitoring information of the Lithium-ion batteries is influenced by variable operation conditions. Many health assessment approaches acquire the battery monitoring information to assess the battery health status. However, these approaches have poor adaptability under variable operation conditions. This paper presents a new health assessment approach of the Lithium-ion batteries under variable operation conditions. Specifically, it extracts the geometrical characteristics of charging and discharging curves of the lithium-ion batteries. Furthermore, it adapts a multiple dimensionality reduction approach based on the locally linear embedding and Isomap. Moreover, the synthetical correlation coefficient is proposed to evaluate the ability of the method to be immune to variable operation conditions. Finally, the example illustrates the effectiveness of the proposed method.

源语言	英语
主期刊名	Machine Learning for Cyber Security - Third International Conference, ML4CS 2020, Proceedings
编辑	Xiaofeng Chen, Hongyang Yan, Qiben Yan, Xiangliang Zhang
出版商	Springer Science and Business Media Deutschland GmbH
页	190-200
页数	11
ISBN（印刷版）	9783030624590
DOI	https://doi.org/10.1007/978-3-030-62460-6_17
出版状态	已出版 - 2020
活动	3rd International Conference on Machine Learning for Cyber Security, ML4CS 2020 - Guangzhou, 中国期限: 8 10月 2020 → 10 10月 2020

出版系列

姓名	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
卷	12487 LNCS
ISSN（印刷版）	0302-9743
ISSN（电子版）	1611-3349

会议

会议	3rd International Conference on Machine Learning for Cyber Security, ML4CS 2020
国家/地区	中国
市	Guangzhou
时期	8/10/20 → 10/10/20

联合国可持续发展目标

此成果有助于实现下列可持续发展目标：

可持续发展目标 7 经济适用的清洁能源

访问文件

10.1007/978-3-030-62460-6_17

其它文件与链接

链接到 Scopus 的出版物

引用此

Hong, S., & Zeng, Y. (2020). A New Health Assessment Approach of Lithium-Ion Batteries Under Variable Operation Conditions. 在 X. Chen, H. Yan, Q. Yan, & X. Zhang (编辑), Machine Learning for Cyber Security - Third International Conference, ML4CS 2020, Proceedings (页码 190-200). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 12487 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-62460-6_17

Hong, Sheng ; Zeng, Yining. / A New Health Assessment Approach of Lithium-Ion Batteries Under Variable Operation Conditions. Machine Learning for Cyber Security - Third International Conference, ML4CS 2020, Proceedings. 编辑 / Xiaofeng Chen ; Hongyang Yan ; Qiben Yan ; Xiangliang Zhang. Springer Science and Business Media Deutschland GmbH, 2020. 页码 190-200 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{eef552134ebd4a93847ab00920451cb7,

title = "A New Health Assessment Approach of Lithium-Ion Batteries Under Variable Operation Conditions",

abstract = "The monitoring information of the Lithium-ion batteries is influenced by variable operation conditions. Many health assessment approaches acquire the battery monitoring information to assess the battery health status. However, these approaches have poor adaptability under variable operation conditions. This paper presents a new health assessment approach of the Lithium-ion batteries under variable operation conditions. Specifically, it extracts the geometrical characteristics of charging and discharging curves of the lithium-ion batteries. Furthermore, it adapts a multiple dimensionality reduction approach based on the locally linear embedding and Isomap. Moreover, the synthetical correlation coefficient is proposed to evaluate the ability of the method to be immune to variable operation conditions. Finally, the example illustrates the effectiveness of the proposed method.",

keywords = "Health assessment, Isomap, Lithium-ion battery, Locally linear embedding",

author = "Sheng Hong and Yining Zeng",

note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 3rd International Conference on Machine Learning for Cyber Security, ML4CS 2020 ; Conference date: 08-10-2020 Through 10-10-2020",

year = "2020",

doi = "10.1007/978-3-030-62460-6\_17",

language = "英语",

isbn = "9783030624590",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "190--200",

editor = "Xiaofeng Chen and Hongyang Yan and Qiben Yan and Xiangliang Zhang",

booktitle = "Machine Learning for Cyber Security - Third International Conference, ML4CS 2020, Proceedings",

address = "德国",

}

Hong, S & Zeng, Y 2020, A New Health Assessment Approach of Lithium-Ion Batteries Under Variable Operation Conditions. 在 X Chen, H Yan, Q Yan & X Zhang (编辑), Machine Learning for Cyber Security - Third International Conference, ML4CS 2020, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 卷 12487 LNCS, Springer Science and Business Media Deutschland GmbH, 页码 190-200, 3rd International Conference on Machine Learning for Cyber Security, ML4CS 2020, Guangzhou, 中国, 8/10/20. https://doi.org/10.1007/978-3-030-62460-6_17

A New Health Assessment Approach of Lithium-Ion Batteries Under Variable Operation Conditions. / Hong, Sheng; Zeng, Yining.
Machine Learning for Cyber Security - Third International Conference, ML4CS 2020, Proceedings. 编辑 / Xiaofeng Chen; Hongyang Yan; Qiben Yan; Xiangliang Zhang. Springer Science and Business Media Deutschland GmbH, 2020. 页码 190-200 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 12487 LNCS).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - A New Health Assessment Approach of Lithium-Ion Batteries Under Variable Operation Conditions

AU - Hong, Sheng

AU - Zeng, Yining

PY - 2020

Y1 - 2020

N2 - The monitoring information of the Lithium-ion batteries is influenced by variable operation conditions. Many health assessment approaches acquire the battery monitoring information to assess the battery health status. However, these approaches have poor adaptability under variable operation conditions. This paper presents a new health assessment approach of the Lithium-ion batteries under variable operation conditions. Specifically, it extracts the geometrical characteristics of charging and discharging curves of the lithium-ion batteries. Furthermore, it adapts a multiple dimensionality reduction approach based on the locally linear embedding and Isomap. Moreover, the synthetical correlation coefficient is proposed to evaluate the ability of the method to be immune to variable operation conditions. Finally, the example illustrates the effectiveness of the proposed method.

AB - The monitoring information of the Lithium-ion batteries is influenced by variable operation conditions. Many health assessment approaches acquire the battery monitoring information to assess the battery health status. However, these approaches have poor adaptability under variable operation conditions. This paper presents a new health assessment approach of the Lithium-ion batteries under variable operation conditions. Specifically, it extracts the geometrical characteristics of charging and discharging curves of the lithium-ion batteries. Furthermore, it adapts a multiple dimensionality reduction approach based on the locally linear embedding and Isomap. Moreover, the synthetical correlation coefficient is proposed to evaluate the ability of the method to be immune to variable operation conditions. Finally, the example illustrates the effectiveness of the proposed method.

KW - Health assessment

KW - Isomap

KW - Lithium-ion battery

KW - Locally linear embedding

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DO - 10.1007/978-3-030-62460-6_17

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SN - 9783030624590

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 190

EP - 200

BT - Machine Learning for Cyber Security - Third International Conference, ML4CS 2020, Proceedings

A2 - Chen, Xiaofeng

A2 - Yan, Hongyang

A2 - Yan, Qiben

A2 - Zhang, Xiangliang

PB - Springer Science and Business Media Deutschland GmbH

T2 - 3rd International Conference on Machine Learning for Cyber Security, ML4CS 2020

Y2 - 8 October 2020 through 10 October 2020

ER -

Hong S, Zeng Y. A New Health Assessment Approach of Lithium-Ion Batteries Under Variable Operation Conditions. 在 Chen X, Yan H, Yan Q, Zhang X, 编辑, Machine Learning for Cyber Security - Third International Conference, ML4CS 2020, Proceedings. Springer Science and Business Media Deutschland GmbH. 2020. 页码 190-200. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-62460-6_17

A New Health Assessment Approach of Lithium-Ion Batteries Under Variable Operation Conditions

摘要

出版系列

会议

联合国可持续发展目标

访问文件

其它文件与链接

学术指纹

引用此