The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
Micro-Short-Circuit Diagnosis for Series-Connected Lithium-Ion Battery Packs Using Mean-Difference Model
Abstract
Micro-short-circuit (MSC) is a latent risk in power batteries, which may give rise to thermal runaway and even catastrophic safety hazards. The motivation of this paper is to quantitatively analyze MSC in an initial stage, particularly for lithium-ion batteries. To verify the feasibility of the proposed method, an equivalent MSC experiment is carried out. Based on a cell difference model, the cell state of charge (SOC) differences with the mean SOC for a battery pack are estimated by extended Kalman filter. The evaluated SOC difference can track the actual value well. Furthermore, an MSC diagnostic method is developed by employing recursive least squares filter. The method is demonstrated to examine the short-circuit resistance accurately. The results also show that the proposed method requires low computational load for the SOC difference and short-circuit resistance diagnosis.
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Self-citationOnline internal short circuit detection for a large format lithium ion battery
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Metadata
- Authors
- Gao, W., Zheng, Y., Ouyang, M., Li, J., Lai, X., & Hu, X.
- Venue
- IEEE Transactions on Industrial Electronics
- Published
- 2019-03
- Volume
- 66
- Issue
- 3
- Pages
- 2132-2142
- ISSN
- 0278-0046 (ISSN-L)
- 1557-9948
- OpenAlex
- W2805771039
- Cited by
- 267
- References
- 28
- FWCI
- 11.30
- Type
- journal article
- Language
- en
- Open access
- closed
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- Gao, W., Zheng, Y., Ouyang, M., Li, J., Lai, X., & Hu, X. (2019). Micro-Short-Circuit Diagnosis for Series-Connected Lithium-Ion Battery Packs Using Mean-Difference Model. IEEE Transactions on Industrial Electronics. https://doi.org/10.1109/tie.2018.2838109
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