储能科学与技术 ›› 2024, Vol. 13 ›› Issue (4): 1197-1204.doi: 10.19799/j.cnki.2095-4239.2023.0827

• 电池智能制造、在线监测与原位分析专刊 • 上一篇    下一篇

金属异物缺陷演化特性及其对产线 K 值的影响机制

袁悦博1(), 王贺武1(), 孔祥栋2, 蒲明伟3, 孙玉坤3, 韩雪冰1, 欧阳明高1   

  1. 1.清华大学车辆与运载学院,北京 100084
    2.四川赛鸥科技有限公司
    3.四川新能源汽车创新中心有限公司,四川 宜宾 644000
  • 收稿日期:2023-11-16 修回日期:2023-12-01 出版日期:2024-04-26 发布日期:2024-04-22
  • 通讯作者: 王贺武 E-mail:yuanyb19@mails.tsinghua.edu.cn;wanghw@tsinghua.edu.cn
  • 作者简介:袁悦博(1996—),男,博士研究生,研究方向为锂离子电池缺陷演变机理与检测方法,E-mail:yuanyb19@mails.tsinghua.edu.cn
  • 基金资助:
    国家自然科学基金青年科学基金项目(52107226);宜宾三江新区“首席专家”科技计划项目(2023SJXQSXZJ001)

Evolution characteristics of metal foreign matter defects and their influence on the K-value of production lines

Yuebo YUAN1(), Hewu WANG1(), Xiangdong KONG2, Mingwei PU3, Yukun SUN3, Xuebing HAN1, Minggao OUYANG1   

  1. 1.School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China
    2.Sichuan Cell Technology Co. , Ltd
    3.Sichuan New Energy Vehicle Innovation Center, Co. , Ltd, Yibin 644000, Sichuan, China
  • Received:2023-11-16 Revised:2023-12-01 Online:2024-04-26 Published:2024-04-22
  • Contact: Hewu WANG E-mail:yuanyb19@mails.tsinghua.edu.cn;wanghw@tsinghua.edu.cn

摘要:

电池制造过程出现的缺陷问题会极大影响电池产品的安全性等,其中产线金属异物侵入可能导致自发性内短路甚至引发热失控,然而目前关于在电池内部的演化机理及相应的外在表征的研究较少,尤其是针对微小金属异物的研究。因此本研究在电池中植入百微米直径铜颗粒,模拟产线金属异物侵入形成缺陷电池,分析了缺陷电池内短路电流特征,拆解研究了内短路区域的微观结构,通过模型仿真了内短路区域的电位分布,综合解释了缺陷对产线关键检测指标K值(电压下降率)的影响规律与机制,并在实际试制线大容量电池上进行了验证。相关研究成果可用于提高产线缺陷检出率,预防潜在的安全事故。研究结果表明,铜颗粒等金属异物侵入电池后,可能导致正极-颗粒-负极和正极-负极两种模式的内短路,内短路电流在正极中产生的电位梯度可抑制颗粒的进一步溶解,从而使得在K值测试条件下的两种内短路模式均会达到平衡状态。两种模式的内短路程度相近,内短路电流处在0.1~1 mA量级。相同的内短路电流对于不同容量单体的K值影响不同,产线上为保证检测效果,随着电池产品容量的增加,K值检测阈值及正常电池的基准值需要相应降低。

关键词: 锂离子电池, 智能制造, 金属异物, 缺陷检测, K

Abstract:

Defects arising during the battery manufacturing process can significantly compromise the safety of battery production. Among these, the intrusion of metal foreign bodies into the production line poses a risk of spontaneous internal short circuits (ISCs) or even thermal runaway. Despite the critical nature of this issue, research on the evolution mechanism of battery defects, particularly those involving small metal foreign bodies, remains scant. This study introduces hundred-micron diameter copper particles into batteries to simulate the intrusion of metal foreign bodies in the production line, thereby generating defective batteries. It then analyzes the ISC current characteristics of these batteries, disassembles them to examine the microstructure of the ISC regions, and develops a simulation model to assess the potential distribution within these regions. The study comprehensively elucidates the influence and mechanisms of defects on the critical detection indicator K-value (voltage drop rate) in the production line, with verification conducted on high-capacity batteries in an actual pilot line. The findings contribute to enhancing defect detection accuracy and preventing potential safety hazards. The results demonstrate that the intrusion of metal foreign bodies, such as copper particles, can precipitate ISC in two distinct modes: cathode-particle-anode and cathode-anode, each indicating different current paths and potential distributions. The ISC current generates a potential gradient in the cathode, reducing the particle's potential and hindering further dissolution. Consequently, the expansion of the ISC region ceases, stabilizing both ISC modes under K-value test conditions. The ISC severity is comparable across both modes, with current levels ranging between 0.1~1 mA. Given the stability of the ISC current, its impact on the K-value can be quantified via the differential voltage slope. The K-value increase attributable to ISC is inversely proportional to battery capacity; in a 100 Ah battery, a 1 mA ISC current has a limited effect on the K-value, increasing it by only 0.01 mV/h. To maintain defect detection precision on the production line, both the K-value detection threshold and the reference values for normal batteries should be adjusted downward as battery capacity increases.

Key words: Li-ion battery, intelligent manufacturing, metal foreign matter, defect detection, K-value

中图分类号: