The DOI matches its Crossref record; 201 of the 201 references it cites were found in a registry or an index.
Internal short circuit mechanisms, experimental approaches and detection methods of lithium-ion batteries for electric vehicles: A review
Abstract
Abstract Energy security, environmental concerns, and the upgrading of automobile industry are the driving trifecta of the rapid development of electric vehicles (EVs). Lithium-ion batteries (LIBs) have become the primary power source for EVs, given their high energy/power density and long service lifetime. However, safety is still a big challenge facing the population of LIBs. Internal short circuit (ISC) is one of the root causes for the failure of LIBs, whereas the mechanism of ISC formation and evolution is still unclear. This paper provides a comprehensive review of formation mechanisms, evolution framework, experimental approaches, detection methods and mitigation strategies of ISC in LIBs. Learning from the typical safety accidents of LIBs, ISC primarily which caused by typical factors is intensively investigated. Later, the behavior and evolution framework of ISC are profoundly elaborated. The ISC experimental approaches are systematically classified into conventional experimental approaches and novel experimental approaches, and their advantages and drawbacks are summarized in detail, respectively. Further, ISC detection methods including offline and online detection methods are comprehensively analyzed. Finally, an insight into the research perspective of ISC mitigation is provided.
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Cites
Toward Safe Lithium Metal Anode in Rechargeable Batteries: A Review
Cheng, X.-B., Zhang, R., Zhao, C.-Z., & Zhang, Q. (2017) · Chemical Reviews · doi:10.1021/acs.chemrev.7b00115 · Cited by 6,197
A review on the key issues for lithium-ion battery management in electric vehicles
Lu, L., Han, X., Li, J., Hua, J., & Ouyang, M. (2013) · Journal of Power Sources · doi:10.1016/j.jpowsour.2012.10.060 · Cited by 4,837
Thermal runaway mechanism of lithium ion battery for electric vehicles: A review
Feng, X., Ouyang, M., Liu, X., Lu, L., Xia, Y., & He, X. (2018) · Energy Storage Materials · doi:10.1016/j.ensm.2017.05.013 · Cited by 4,182
A critical review of thermal issues in lithium-ion batteries
Bandhauer, T. M., Garimella, S., & Fuller, T. F. (2011) · Journal of The Electrochemical Society · doi:10.1149/1.3515880 · Cited by 2,192
Challenges and opportunities towards fast-charging battery materials
Liu, Y., Zhu, Y., & Cui, Y. (2019) · Nature Energy · doi:10.1038/s41560-019-0405-3 · Cited by 1,781
Mitigating Thermal Runaway of Lithium-Ion Batteries
Feng, X., Ren, D., He, X., & Ouyang, M. (2020) · Joule · doi:10.1016/j.joule.2020.02.010 · Cited by 1,735
Lithium-ion battery fast charging: A review
Tomaszewska, A., Chu, Z., Feng, X., O'Kane, S., Liu, X., Chen, J., Ji, C., Endler, E., Li, R., Liu, L., et al. (2019) · eTransportation · doi:10.1016/j.etran.2019.100011 · Cited by 1,592
Transition of lithium growth mechanisms in liquid electrolytes
Bai, P., Li, J., Brushett, F. R., & Bazant, M. Z. (2016) · Energy & Environmental Science · doi:10.1039/c6ee01674j · Cited by 1,591
Model-based fault-detection and diagnosis – status and applications
Isermann, R. (2005) · Annual Reviews in Control · doi:10.1016/j.arcontrol.2004.12.002 · Cited by 1,579
Abuse behavior of high-power, lithium-ion cells
Spotnitz, R., & Franklin, J. (2003) · Journal of Power Sources · doi:10.1016/s0378-7753(02)00488-3 · Cited by 1,373
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Qu, Y., Xing, B., Xia, Y., & Zhou, Q. (2024) · eTransportation · doi:10.1016/j.etran.2024.100331 · Cited by 35
Metadata
- Authors
- Zhang, G., Wei, X., Tang, X., Zhu, J., Chen, S., & Dai, H.
- Venue
- Renewable and Sustainable Energy Reviews
- Publisher
- Elsevier BV
- Published
- 2021-05
- Volume
- 141
- Pages
- 110790
- ISSN
- 1364-0321 (ISSN-L)
- OpenAlex
- W3126486041
- Cited by
- 308
- References
- 201
- FWCI
- 14.75
- Type
- journal article
- Language
- en
- Open access
- closed
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- Zhang, G., Wei, X., Tang, X., Zhu, J., Chen, S., & Dai, H. (2021). Internal short circuit mechanisms, experimental approaches and detection methods of lithium-ion batteries for electric vehicles: A review. Renewable and Sustainable Energy Reviews. https://doi.org/10.1016/j.rser.2021.110790
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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