锂离子电池缺陷检测技术及失效机理分析研究进展

doi:10.11896/cldb.24100016

材料导报

2025, Vol. 39

Issue (11): 24100016-9 https://doi.org/10.11896/cldb.24100016

无机非金属及其复合材料

锂离子电池缺陷检测技术及失效机理分析研究进展

李龙飞¹, 郑永泉¹, 万旺军^2,*, 徐至宏³, 汪清利⁴, 王琛², 贺馨平¹, 夏新辉¹, 夏阳^1,*

1 浙江工业大学材料科学与工程学院,杭州 310014
2 浙江省检验检疫科学技术研究院,杭州 311215
3 浙江华云清洁能源有限公司,杭州 310008
4 杭州润辉环保能源科技有限公司,杭州 310020

Research Progress in Failure Analysis and Defect Detection of Lithium-ion Batteries

LI Longfei¹, ZHENG Yongquan¹, WAN Wangjun^2,*, XU Zhihong³, WANG Qingli⁴, WANG Chen², HE Xinping¹, XIA Xinhui¹, XIA Yang^1,*

1 College of Materials Science and Engineering, Zhejiang University of Technology, Hangzhou 310014, China
2 Zhejiang Academy of Science and Technology for Inspection & Quarantine, Hangzhou 311215, China
3 Zhejiang Huayun Cleaning Energy Co., Ltd., Hangzhou 310008, China
4 Hangzhou Runhui Environmental Protection Energy Technology Co., Ltd., Hangzhou 310020, China

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摘要锂离子电池失效分析和检测技术对认识电池失效机理、监测电池状态、诊断和预警电池故障、评估电池寿命和安全性意义重大,同时对锂离子电池的设计开发和性能提升具有指导价值。本文从“材料-电芯-模组-管理系统”多层级角度对锂离子电池缺陷检测方法进行介绍,并以电池“内生性”失效和“外源性”失效的双视角角度对锂离子电池的失效进行分类,详细讨论了电池缺陷检测技术在锂离子电池双视角失效分析方面的应用。最后,本文提出将失效检测技术与机器学习算法相结合,构建快速高通量检测新体系,并对未来电池失效分析技术进行展望,以期为高安全锂离子电池技术的发展提供重要参考。

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	李龙飞
	郑永泉
	万旺军
	徐至宏
	汪清利
	王琛
	贺馨平
	夏新辉
	夏阳

关键词: 锂离子电池失效分析缺陷检测多层级双视角

Abstract: Failure analysis and defect detection technology of lithium-ion batteries play important roles in revealing the failure mechanism, monitoring battery status, diagnosing and warning battery failure, evaluating battery life and safety. Meanwhile, battery failure analysis and defect detection technology significantly guide the design and development of high-performance lithium-ion batteries. This review first introduces the battery defect detection methods from the multi-level perspective of “battery materials-single cell-battery module-battery management system”. It second classifies the battery failure mechanisms from the dual perspectives of “"endogenous" failure and "exogenous" failure” with practical application cases. Finally the paper proposes to combine failure detection technology and machine learning algorithm to build a new system of fast and high-throughput detection strategy, and outlooks the development of battery failure analysis technology, hoping to provide important information and insights for the evolvement of high-safety lithium-ion battery technology.

Key words: lithium-ion battery failure analysis defect detection multi-level perspective dual perspective

发布日期: 2025-05-29

ZTFLH:

TK911

基金资助: 浙江省“领雁”计划项目(2023C01231)

通讯作者: *万旺军,硕士,杭州海关技术中心国家危险化学品检测重点实验室主任、研究员,主要从事危险货物分类鉴定、锂离子电池安全性评估等。181892505@qq.com
夏阳,博士,浙江工业大学材料科学与工程学院教授、博士研究生导师。主要从事先进二次电池关键材料和技术的基础理论和应用研究工作。nanoshine@zjut.edu.cn

作者简介: 李龙飞,2023年6月于桂林理工大学获得工学学士学位。现为浙江工业大学材料科学与工程学院硕士研究生,在夏阳教授的指导下进行研究,主要研究领域为高比能锂离子电池材料与器件。

引用本文:

李龙飞, 郑永泉, 万旺军, 徐至宏, 汪清利, 王琛, 贺馨平, 夏新辉, 夏阳. 锂离子电池缺陷检测技术及失效机理分析研究进展[J]. 材料导报, 2025, 39(11): 24100016-9.
LI Longfei, ZHENG Yongquan, WAN Wangjun, XU Zhihong, WANG Qingli, WANG Chen, HE Xinping, XIA Xinhui, XIA Yang. Research Progress in Failure Analysis and Defect Detection of Lithium-ion Batteries. Materials Reports, 2025, 39(11): 24100016-9.

链接本文:

https://www.mater-rep.com/CN/10.11896/cldb.24100016 或 https://www.mater-rep.com/CN/Y2025/V39/I11/24100016

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