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Improved Parameter Identification for Lithium-Ion Batteries Based on Complex-Order Beetle Swarm Optimization Algorithm

delete2023-02-09
delete6
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OA
AI
X
Xiaohua Zhang
H
Haolin Li
W
Wenfeng Zhang
A
António M. Lopes *
X
Xiaobo Wu
陈丽萍 cover
陈丽萍 (Liping Chen)
DOI：10.3390/mi14020413delete
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Abstract

Abstract

En 中文
With the aim of increasing the model accuracy of lithium-ion batteries (LIBs), this paper presents a complex-order beetle swarm optimization (CBSO) method, which employs complex-order (CO) operator concepts and mutation into the traditional beetle swarm optimization (BSO). Firstly, a fractional-order equivalent circuit model of LIBs is established based on electrochemical impedance spectroscopy (EIS). Secondly, the CBSO is used for model parameters' identification, and the model accuracy is verified by simulation experiments. The root-mean-square error (RMSE) and maximum absolute error (MAE) optimization metrics show that the model accuracy with CBSO is superior when compared with the fractional-order BSO.
Keywords:
FO equivalent circuit
parameter identification
beetle swarm optimization
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Journal

Micromachines cover
Micromachines
IF:
3
Papers:
1.4W
Citations:
2.9W

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