The DOI matches its Crossref record; 147 of the 147 references it cites were found in a registry or an index.
A review of modeling, acquisition, and application of lithium-ion battery impedance for onboard battery management
Abstract
Abstract Impedance is closely related to the internal physical and chemical processes of lithium-ion batteries. And the properties of the processes can be characterized and thus more detailed information be provided based on it. In the past decades, the impedance is frequently reported as a powerful tool used in the field of lithium-ion battery state estimation and diagnosis. This paper reviews more than 170 papers and organizes the related research according to three themes of impedance modeling, acquisition, and application under the premise of electric vehicle implementation. The strength and weaknesses of the research in each theme are discussed. Based on the research, the possibility and the value of impedance in onboard battery management are revealed. However, challenges are still faced due to the cost limitations, the complex vehicular conditions, and the time-varying battery states. The unsolved issues are summarized in the conclusion. To realize a more smart battery management system with the impedance, more significant work is still needed.
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Cites
Impedance Spectroscopy: Theory, Experiment, and Applications
(2005) · Wiley eBooks · doi:10.1002/0471716243 · Cited by 5,322
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
Impedance spectroscopy theory, experiment, and applications
(2005) · Choice Reviews Online · doi:10.5860/choice.43-0327 · Cited by 2,299
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
Hannan, M. A., Lipu, M. S. H., Hussain, A., & Mohamed, A. (2017) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2017.05.001 · Cited by 2,005
Kinetics of rapid electrode reactions
Randles, J. E. B. (1947) · Discussions of the Faraday Society · doi:10.1039/df9470100011 · Cited by 1,884
Macdonald, J. R. (1992) · Annals of Biomedical Engineering · doi:10.1007/bf02368532 · Cited by 1,166
Xiong, R., Li, L., & Tian, J. (2018) · Journal of Power Sources · doi:10.1016/j.jpowsour.2018.10.019 · Cited by 1,017
Reflections on the history of electrochemical impedance spectroscopy
Macdonald, D. D. (2006) · Electrochimica Acta · doi:10.1016/j.electacta.2005.02.107 · Cited by 1,001
Waag, W., Käbitz, S., & Sauer, D. U. (2013) · Applied Energy · doi:10.1016/j.apenergy.2012.09.030 · Cited by 987
Cited by
Hu, W., Peng, Y., Wei, Y., & Yang, Y. (2023) · The Journal of Physical Chemistry C · doi:10.1021/acs.jpcc.3c00033 · Cited by 429
Jiang, B., Zhu, J., Wang, X., Wei, X., Shang, W., & Dai, H. (2022) · Applied Energy · doi:10.1016/j.apenergy.2022.119502 · Cited by 367
Self-citationChallenges and development of lithium-ion batteries for low temperature environments
Piao, N., Gao, X., Yang, H., Guo, Z., Hu, G., Cheng, H.-M., & Li, F. (2022) · eTransportation · doi:10.1016/j.etran.2021.100145 · Cited by 324
Zhang, G., Wei, X., Tang, X., Zhu, J., Chen, S., & Dai, H. (2021) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2021.110790 · Cited by 308
Self-citationGuo, R., & Shen, W. (2021) · Vehicles · doi:10.3390/vehicles4010001 · Cited by 121
Metadata
- Authors
- Wang, X., Wei, X., Zhu, J., Dai, H., Zheng, Y., Xu, X., & Chen, Q.
- Venue
- eTransportation
- Publisher
- Elsevier BV
- Published
- 2021-02
- Volume
- 7
- Pages
- 100093
- ISSN
- 2590-1168 (ISSN-L)
- OpenAlex
- W3106603010
- Cited by
- 451
- References
- 147
- FWCI
- 19.27
- Type
- journal article
- Language
- en
- Open access
- closed
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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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