The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Lithium-ion battery aging mechanisms and diagnosis method for automotive applications: Recent advances and perspectives
Abstract
Abstract Lithium-ion batteries decay every time as it is used. Aging-induced degradation is unlikely to be eliminated. The aging mechanisms of lithium-ion batteries are manifold and complicated which are strongly linked to many interactive factors, such as battery types, electrochemical reaction stages, and operating conditions. In this paper, we systematically summarize mechanisms and diagnosis of lithium-ion battery aging. Regarding the aging mechanism, effects of different internal side reactions on lithium-ion battery degradation are discussed based on the anode, cathode, and other battery structures. The influence of different external factors on the aging mechanism is explained, in which temperature can exert the greatest impact compared to other external factors. As for aging diagnosis, three widely-used methods are discussed: disassembly-based post-mortem analysis, curve-based analysis, and model-based analysis. Generally, the post-mortem analysis is employed for cross-validation while the curve-based analysis and the model-based analysis provide quantitative analysis. The challenges in the use of quantitative diagnosis and on-board diagnosis on battery aging are also discussed, based on which insights are provided for developing online battery aging diagnosis and battery health management in the next generation of intelligent battery management systems (BMSs).
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Cites
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A Data-Driven Method for Extracting Aging Features to Accurately Predict the Battery Health
Xiong, R., Sun, Y., Wang, C., Tian, J., Chen, X., Li, H., & Zhang, Q. (2023) · Energy storage materials · doi:10.1016/j.ensm.2023.02.034 · Cited by 190
Self-citationIoB: Internet-of-batteries for electric Vehicles–Architectures, opportunities, and challenges
Li, H., Bin Kaleem, M., Liu, Z., Wu, Y., Liu, W., & Huang, Z. (2023) · Green Energy and Intelligent Transportation · doi:10.1016/j.geits.2023.100128 · Cited by 95
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Aging behavior and mechanisms of lithium-ion battery under multi-aging path
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Metadata
- Authors
- Xiong, R., Pan, Y., Shen, W., Li, H., & Sun, F.
- Venue
- Renewable and Sustainable Energy Reviews
- Publisher
- Elsevier BV
- Published
- 2020-10
- Volume
- 131
- Pages
- 110048
- ISSN
- 1364-0321 (ISSN-L)
- OpenAlex
- W3043289899
- Cited by
- 725
- References
- 12
- FWCI
- 28.73
- Type
- journal article
- Language
- en
- Open access
- closed
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- Xiong, R., Pan, Y., Shen, W., Li, H., & Sun, F. (2020). Lithium-ion battery aging mechanisms and diagnosis method for automotive applications: Recent advances and perspectives. Renewable and Sustainable Energy Reviews. https://doi.org/10.1016/j.rser.2020.110048
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