The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
A new on-line method for lithium plating detection in lithium-ion batteries
Abstract
Abstract The desire to move towards the rapid charging of lithium-ion batteries has motivated many researchers to understand the underpinning degradation mechanisms as a precursor for the design of novel models and control algorithms to help mitigate their occurrence. It is widely reported that lithium plating is a significant ageing mechanism that occurs when charging the battery at low temperatures, high C-rates and high state of charge (SOC). There are multiple efforts embracing the measurement of different parameters during charging, such as battery voltage and current, that may collectively provide critical information useful for the detection of lithium plating. Much of this research is focussed on the post-processing of such data after completion of charge to infer the onset of lithium plating. This study aims to extend recent work, by proposing a new method of lithium plating detection, based on an estimation of cell impedance. This approach is able to operate in real-time during charging and therefore transferable to the battery management system (BMS). Experimental results highlight that the proposed method is highly sensitive and capable of effectively detecting the onset of lithium plating in real-time, underpinning the design of future optimal charging strategies to minimize lithium plating.
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Waag, W., Käbitz, S., & Sauer, D. U. (2013) · Applied Energy · doi:10.1016/j.apenergy.2012.09.030 · Cited by 987 · cited 10×
“As discussed within [28], these processes can be individually identified by using EIS since each of them has a different time constant or frequency range of excitation.”
BackgroundMethodInfluentialPinson, M. B., & Bazant, M. Z. (2013) · Journal of The Electrochemical Society · doi:10.1149/2.044302jes · Cited by 946
Petzl, M., & Danzer, M. A. (2014) · Journal of Power Sources · doi:10.1016/j.jpowsour.2013.12.060 · Cited by 511
Nonlinear aging of cylindrical lithium-ion cells linked to heterogeneous compression
Bach, T. C., Schuster, S. F., Fleder, E., Müller, J., Brand, M. J., Lorrmann, H., Jossen, A., & Sextl, G. (2016) · Journal of Energy Storage · doi:10.1016/j.est.2016.01.003 · Cited by 296
Ecker, M., Shafiei Sabet, P., & Sauer, D. U. (2017) · Applied Energy · doi:10.1016/j.apenergy.2017.08.034 · Cited by 181
Cited by
Lithium Plating Mechanism, Detection, and Mitigation in Lithium-Ion Batteries
Lin, X., Khosravinia, K., Hu, X., Li, J., & Lu, W. (2021) · Progress in Energy and Combustion Science · doi:10.1016/j.pecs.2021.100953 · Cited by 490
Wang, X., Wei, X., Zhu, J., Dai, H., Zheng, Y., Xu, X., & Chen, Q. (2021) · eTransportation · doi:10.1016/j.etran.2020.100093 · Cited by 451
Hu, W., Peng, Y., Wei, Y., & Yang, Y. (2023) · The Journal of Physical Chemistry C · doi:10.1021/acs.jpcc.3c00033 · Cited by 429
Challenges 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
End-of-life or second-life options for retired electric vehicle batteries
Zhu, J., Mathews, I., Ren, D., Li, W., Cogswell, D., Xing, B., Sedlatschek, T., Kantareddy, S. N. R., Yi, M., Gao, T., et al. (2021) · Cell Reports Physical Science · doi:10.1016/j.xcrp.2021.100537 · Cited by 306
Metadata
- Authors
- Koleti, U. R., Dinh, T. Q., & Marco, J.
- Venue
- Journal of Power Sources
- Publisher
- Elsevier BV
- Published
- 2020-03
- Volume
- 451
- Pages
- 227798
- ISSN
- 0378-7753 (ISSN-L)
- OpenAlex
- W3004302587
- Cited by
- 177
- References
- 5
- FWCI
- 7.80
- Type
- journal article
- Language
- en
- Open access
- closed
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- Koleti, U. R., Dinh, T. Q., & Marco, J. (2020). A new on-line method for lithium plating detection in lithium-ion batteries. Journal of Power Sources. https://doi.org/10.1016/j.jpowsour.2020.227798
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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.
