The DOI matches its Crossref record; 190 of the 190 references it cites were found in a registry or an index.
Mechanism, modeling, detection, and prevention of the internal short circuit in lithium-ion batteries: Recent advances and perspectives
Abstract
Abstract Safety concerns are the main obstacle to large-scale application of lithium-ion batteries (LIBs), and thus, improving the safety of LIBs is receiving global attention. Within battery systems, the internal short circuit (ISC) is considered to be a severe hazard, as it may result in catastrophic safety failures, such as thermal runaway. Considering this, we provide a comprehensive review on the mechanism and evolutionary process of ISC, including modeling and simulation experiments and the methods of detection and diagnosis. First, ISC types and the inducing mechanism under various inducements are analyzed, and the evolution process of ISC is divided into three stages according to electrical and thermal characteristics. Second, eleven existing ISC substitute experimental methods are listed in detail, and three coupling models of electric-thermal-ISC models are introduced to simulate the characteristics of ISC. Third, existing ISC detection methods are reviewed in detail, divided into six categories. Moreover, we propose methods for ISC detection under four special conditions: ISC detection for the cells before grouping, ISC detection method during electric vehicle dormancy, ISC detection based on equilibrium electric quantity compensation to address negative impact of the equalization function of the battery management system on ISC detection, and effective fault tree diagnosis for the joint identification and early warning of multiple battery faults. Fourth, existing ISC prevention methods are reviewed. Finally, the key technologies of ISC are prospected, revealing that the development of big data and artificial intelligence technology will promote the accuracy and timeliness of ISC detection.
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Self-citationBuilding Practical High‐Voltage Cathode Materials for Lithium‐Ion Batteries
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End-of-life or second-life options for retired electric vehicle batteries
Zhu, J., Mathews, I., Ren, D., Li, W., Cogswell, D., Xing, B., Sedlatschek, T., Kantareddy, S. N. R., Yi, M., Gao, T., et al. (2021) · Cell Reports Physical Science · doi:10.1016/j.xcrp.2021.100537 · Cited by 306
Battery Safety: Machine Learning-Based Prognostics
Zhao, J., Feng, X., Pang, Q., Fowler, M., Lian, Y., Ouyang, M., & Burke, A. F. (2024) · Progress in Energy and Combustion Science · doi:10.1016/j.pecs.2023.101142 · Cited by 216
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Metadata
- Authors
- Lai, X., Jin, C., Yi, W., Han, X., Feng, X., Zheng, Y., & Ouyang, M.
- Venue
- Energy Storage Materials
- Publisher
- Elsevier BV
- Published
- 2021-03
- Volume
- 35
- Pages
- 470-499
- ISSN
- 2405-8289 (ISSN-L)
- 2405-8297
- OpenAlex
- W3106880287
- Cited by
- 438
- References
- 190
- FWCI
- 14.87
- Type
- journal article
- Language
- en
- Open access
- closed
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- Lai, X., Jin, C., Yi, W., Han, X., Feng, X., Zheng, Y., & Ouyang, M. (2021). Mechanism, modeling, detection, and prevention of the internal short circuit in lithium-ion batteries: Recent advances and perspectives. Energy Storage Materials. https://doi.org/10.1016/j.ensm.2020.11.026
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