The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Research progress, challenges and prospects of fault diagnosis on battery system of electric vehicles
Abstract
Abstract Due to the limited capacity and voltage of single battery cell, the battery system for electric vehicles often consists of hundreds or thousands of single cells in series and parallel connection. The inconsistency of individual cell in capacity, voltage, internal resistance, etc., and their coupling effects with aging make the battery system fail frequently, which brings great challenges to the safe and reliable operation of the battery system. This paper discusses the research progress of battery system faults and diagnosis from sensors, battery and components, and actuators: (1) the causes and influences of sensor fault, actuator fault, internal/external short circuit fault, overcharge/over-discharge fault, connection fault, inconsistency, insulation fault, thermal management system fault are analyzed; (2) the fault diagnosis methods and their application characteristics in up-to-date battery system fault research are discussed, and the research trends of battery system fault diagnosis are sorted out; (3) Further, the future challenges and potential research directions of battery system fault diagnosis driven by new technologies such as big data are discussed. Finally, the summarization of whole paper is presented.
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Cites
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
A comparative study of equivalent circuit models for Li-ion batteries
Hu, X., Li, S., & Peng, H. (2012) · Journal of Power Sources · doi:10.1016/j.jpowsour.2011.10.013 · Cited by 2,179
Production caused variation in capacity aging trend and correlation to initial cell performance
Baumhöfer, T., Brühl, M., Rothgang, S., & Sauer, D. U. (2014) · Journal of Power Sources · doi:10.1016/j.jpowsour.2013.08.108 · Cited by 421
Internal short circuit detection for battery pack using equivalent parameter and consistency method
Ouyang, M., Zhang, M., Feng, X., Lu, L., Li, J., He, X., & Zheng, Y. (2015) · Journal of Power Sources · doi:10.1016/j.jpowsour.2015.06.087 · Cited by 309
Cited by
Nyamathulla, S., & Dhanamjayulu, C. (2024) · Journal of Energy Storage · doi:10.1016/j.est.2024.111179 · Cited by 518
Li, X., Yuan, C., Wang, Z., & Xie, J. (2022) · Energy · doi:10.1016/j.energy.2021.122206 · Cited by 56
Metadata
- Authors
- Xiong, R., Sun, W., Yu, Q., & Sun, F.
- Venue
- Applied Energy
- Publisher
- Elsevier BV
- Published
- 2020-12
- Volume
- 279
- Pages
- 115855
- ISSN
- 0306-2619 (ISSN-L)
- OpenAlex
- W3087709927
- Cited by
- 481
- References
- 4
- FWCI
- 20.01
- Type
- journal article
- Language
- en
- Open access
- closed
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- Xiong, R., Sun, W., Yu, Q., & Sun, F. (2020). Research progress, challenges and prospects of fault diagnosis on battery system of electric vehicles. Applied Energy. https://doi.org/10.1016/j.apenergy.2020.115855
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
