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Cited by 265

The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.

A comparative study of global optimization methods for parameter identification of different equivalent circuit models for Li-ion batteries

Lai, Xin, Gao, Wenkai, Zheng, Yuejiu, Ouyang, Minggao, Li, Jianqiu, Han, Xuebing, Zhou, Long·2019·Electrochimica Acta
DOI 10.1016/j.electacta.2018.11.134
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Abstract

Abstract A suitable model structure and matched model parameters are prerequisites for the precise estimation of the battery states. Previous studies pay little attention to whether a parameter identification method is suitable for a model. In this study, a comparative study is conducted by implementing model parameter optimization for nine equivalent circuit models using nine optimizers in the entire SOC area. The following conclusions are drawn: (1) PNGV and the exact algorithms are an ideal combination in the low SOC area (0%–20%). (2) In the high SOC area (20–100%), exact algorithms are an ideal choice for the first-order RC models, and PSO is an ideal identification algorithm for second-order RC models. For the third- and fourth-order RC models, firefly algorithm has the highest accuracy with longer identification time. (3) Firefly algorithm has the superior capacity to identify the accurate model parameters and PSO has the best comprehensive performance for on-line parameter identification.

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Metadata

Authors
Lai, X., Gao, W., Zheng, Y., Ouyang, M., Li, J., Han, X., & Zhou, L.
Venue
Electrochimica Acta
Publisher
Elsevier BV
Published
2019-02
Volume
295
Pages
1057-1066
ISSN
0013-4686 (ISSN-L)
DOI
10.1016/j.electacta.2018.11.134
OpenAlex
W2900825030
Cited by
265
References
32
FWCI
10.77
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: A comparative study of global optimization methods for parameter identification of different equivalent circuit models for Li-ion batteries. https://app.cochat.ai/papers/10.1016/j.electacta.2018.11.134
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Lai, X., Gao, W., Zheng, Y., Ouyang, M., Li, J., Han, X., & Zhou, L. (2019). A comparative study of global optimization methods for parameter identification of different equivalent circuit models for Li-ion batteries. Electrochimica Acta. https://doi.org/10.1016/j.electacta.2018.11.134

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.