Multiscale Imaging Techniques for Real-Time, Noninvasive Diagnosis of Li-Ion Battery Failures

被引:3
|
作者
Lee, Mingyu [1 ]
Lee, Jiwon [1 ]
Shin, Yewon [1 ]
Lee, Hongkyung [1 ,2 ]
机构
[1] Daegu Gyeongbuk Inst Sci & Technol DGIST, Dept Energy Sci & Engn, 333 Technojungang Ro,Dalsung Gun, Daegu 42988, South Korea
[2] DGIST, Energy Sci & Engn Res Ctr, 333 Technojungang Ro,Dalsung Gun, Daegu 42988, South Korea
来源
SMALL SCIENCE | 2023年 / 3卷 / 11期
基金
新加坡国家研究基金会;
关键词
battery diagnosis; current distribution; latent defects; lithium batteries; multiscale imaging techniques; LITHIUM-ION; IN-SITU; ELECTRIC VEHICLES; SPATIAL-DISTRIBUTION; GRAPHITE ELECTRODE; AGING MECHANISMS; THERMAL RUNAWAY; FILLING PROCESS; SHORT CIRCUITS; CELLS;
D O I
10.1002/smsc.202300063
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
With the increasing popularity of battery-powered mobility, ensuring the safety and reliability of Li-ion batteries (LIBs) has become critical for manufacturers. Despite advanced manufacturing processes for large-scale Li-ion cells, "latent defects" still unintentionally appear, due to imbalanced battery design, invisible faults, and extreme operating conditions. These defects cause performance degradation and can even lead to battery fires. Hence, early detection of latent defects, along with understanding the influence of cell parameters and operating conditions on battery failure scenarios, is crucial. For straightforward investigations and interpretations, noninvasive and in operando battery imaging techniques and methods have been proposed using X-rays, neutrons, and ultrasound, as these can penetrate active and component materials and cell packaging. Moreover, magnetic-field-guided visualization of the current distribution pattern in cells under a current load has been proposed to identify invisible defects. This review thoroughly examines various imaging techniques for internal batteries, from the atomic and molecular levels in electrode materials and interfaces to macroscale battery systems. By assessing qualitative case studies and newly discovered phenomena, this review provides valuable insights into state-of-the-art noninvasive battery imaging and its potential to improve the safety and reliability of LIB technology. Diagnosing Li secondary batteries using in operando, noninvasive imaging tools is crucial for securing their safety and reliability. Combining X-rays, neutrons, ultrasound, and magnetic fields, multiscale battery imaging through its hierarchy from particle to cell level can provide a comprehensive picture of the structural and chemical information of the battery interior, aiding in understanding various failure scenarios and pinpointing the defect locations.image (c) 2023 WILEY-VCH GmbH
引用
收藏
页数:20
相关论文
共 50 条
  • [41] Towards a more realistic battery model: variational multiscale modeling of Li-ion batteries
    Liu, Lin
    Moradi, Moein
    [J]. SELECTED PROCEEDINGS FROM THE 231ST ECS MEETING, 2017, 77 (11): : 273 - 291
  • [42] Strain imaging of a LiCoO2 cathode in a Li-ion battery
    Matsushita, Yuki
    Osaka, Ryuma
    Butsugan, Kenta
    Takata, Keiji
    [J]. JOURNAL OF CHEMICAL PHYSICS, 2016, 145 (11):
  • [43] High accuracy temperaure-dependent SOC estimation based on real-time parameter identification for rechargeable Li-Ion battery pack
    Park, Jinhyeong
    Bae, Hynsu
    Jang, Sung-Soo
    Na, Woonki
    Kim, Jonghoon
    [J]. THIRTY-FOURTH ANNUAL IEEE APPLIED POWER ELECTRONICS CONFERENCE AND EXPOSITION (APEC 2019), 2019, : 2934 - 2938
  • [44] Parameter identification and co-estimation of state-of-charge of Li-ion battery in real-time on Internet-of-Things platform
    Mondal, Arpita
    Routray, Aurobinda
    Puravankara, Sreeraj
    [J]. JOURNAL OF ENERGY STORAGE, 2022, 51
  • [45] Real-time elastography for noninvasive diagnosis of liver fibrosis
    Kanamoto, Mami
    Shimada, Mitsuo
    Ikegami, Toru
    Imura, Satoru
    Morine, Yuji
    Ikemoto, Tetsuya
    Mori, Hiroki
    Hanaoka, Jun
    Sugimoto, Koji
    Tokunaga, Takuya
    [J]. GASTROENTEROLOGY, 2008, 134 (04) : A828 - A828
  • [46] An omnipotent Li-ion battery charger with multimode control and polarity reversible techniques
    Chen, Jiann-Jong
    Ku, Yi-Tsen
    Yang, Hong-Yi
    Hwang, Yuh-Shyan
    Yu, Cheng-Chieh
    [J]. INTERNATIONAL JOURNAL OF ELECTRONICS, 2016, 103 (07) : 1138 - 1152
  • [47] New Li-Ion battery charger based on charge-pump techniques
    Hwang, Yuh-Shyan
    Wang, Shu-Chen
    Fong-Cheng-Yang
    Chen, Jiann-Jong
    Lee, Wen-Ta
    [J]. 2006 INTERNATIONAL CONFERENCE ON COMMUNICATIONS, CIRCUITS AND SYSTEMS PROCEEDINGS, VOLS 1-4: VOL 1: SIGNAL PROCESSING, 2006, : 2259 - 2262
  • [48] Real-Time State-of-Charge Estimation Using an Embedded Board for Li-Ion Batteries
    Hong, Seonri
    Kang, Moses
    Park, Hwapyeong
    Kim, Jonghoon
    Baek, Jongbok
    [J]. ELECTRONICS, 2022, 11 (13)
  • [49] Predicting the Degradation of Li-ion Battery Using Advanced Machine Learning Techniques
    Li, Yi-Ru
    Chung, Kuan-Jung
    [J]. 2017 12TH INTERNATIONAL MICROSYSTEMS, PACKAGING, ASSEMBLY AND CIRCUITS TECHNOLOGY CONFERENCE (IMPACT), 2017, : 258 - 262
  • [50] Recursive Least Square Estimation Approach to Real-Time Parameter Identification in Li-ion Batteries
    Raihan, Sheikh Arif
    Balasingam, Balakumar
    [J]. 2019 IEEE ELECTRICAL POWER AND ENERGY CONFERENCE (EPEC), 2019,