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Research on Identification Method for Equivalent Circuit Model of Lithium-ion Battery Based on ISBO Algorithm
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Kai HUANG1, 2, Haijian TIAN1, 2, Heng DING1, 2
Journal of Power Supply | 2024, 22(1) : 83 - 93
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Journal of Power Supply | 2024, 22(1): 83-93
• Battery and Energy Storage •
Research on Identification Method for Equivalent Circuit Model of Lithium-ion Battery Based on ISBO Algorithm
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Kai HUANG1, 2, Haijian TIAN1, 2, Heng DING1, 2
Affiliations
  • 1 State Key Lab of Reliability and Intelligence of Electrical Equipment Tianjin 300130 China
  • 2 Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province Tianjin 300130 China
Published: 2024-01-30 doi: 10.13234/j.issn.2095-2805.2024.1.83
Outline
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The parameter identification method for the equivalent circuit model of lithium-ion battery has a great impact on the model accuracy. To solve the problems of low convergence accuracy and slow convergence speed in a satin bowerbird optimization(SBO) algorithm, an improved satin bowerbird optimization (ISBO) algorithm is proposed. The inertial weights, Cauchy mutation, Gaussian mutation and greedy selection strategies are used to improve the convergence accuracy of the ISBO algorithm, and its convergence performance is verified by standard test functions. Based on the battery charging and discharging data, the proposed ISBO algorithm is applied to the parameter identification of the equivalent circuit model of lithium-ion battery. Experimental results show that compared with the SBO and adaptive weight particle swarm optimization algorithms, the ISBO algorithm has a higher accuracy when it is used in identifying the model parameters and the identification accuracy is not affected by the working conditions of battery.

Lithium-ion battery  /  equivalent circuit model  /  model parameter identification  /  improved satin bowerbird opti- mization (ISBO) algorithm
Kai HUANG, Haijian TIAN, Heng DING. Research on Identification Method for Equivalent Circuit Model of Lithium-ion Battery Based on ISBO Algorithm[J]. Journal of Power Supply, 2024 , 22 (1) : 83 -93 . DOI: 10.13234/j.issn.2095-2805.2024.1.83
Funding
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  • Key Natural Science Foundation of Hebei Province(E2017202284)
  • Key Natural Science Foundation of Tianjin(19JCZDJC32100)
  • Natural Science Foundation of Hebei Province(E2019202328)
Appendix
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Year 2024 volume 22 Issue 1
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Article Info
doi: 10.13234/j.issn.2095-2805.2024.1.83
  • Receive Date：2021-08-02
  • Online Date：2025-07-21
  • Published：2024-01-30
Article Data
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History
  • Received：2021-08-02
  • Revised：2021-09-22
  • Accepted：2021-10-09
Funding
Key Natural Science Foundation of Hebei Province(E2017202284)
Key Natural Science Foundation of Tianjin(19JCZDJC32100)
Natural Science Foundation of Hebei Province(E2019202328)
Affiliations
    1 State Key Lab of Reliability and Intelligence of Electrical Equipment Tianjin 300130 China
    2 Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province Tianjin 300130 China
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https://castjournals.cast.org.cn/joweb/dyxb/EN/10.13234/j.issn.2095-2805.2024.1.83
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