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Parameter Identification and SOC Estimation of Lithium Battery Based on Adaptive Dynamic Sliding Window
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Ye ZHU1, Yuanrui CHEN1, Yang CHEN2, Zhenlin WANG3
Electric Drive | 2024, 54(2) : 12 - 20
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Electric Drive | 2024, 54(2): 12-20
Parameter Identification and SOC Estimation of Lithium Battery Based on Adaptive Dynamic Sliding Window
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Ye ZHU1, Yuanrui CHEN1, Yang CHEN2, Zhenlin WANG3
Affiliations
  • 1 School of Electric Power，South China University of Technology，Guangzhou 510641，Guangdong，China
  • 2 School of Intelligent Science and Engineering，Harbin Engineering University，Harbin 150000，Heilongjiang，China
  • 3 School of Electronic Engineering，South China Agricultural University，Guangzhou 510642，Guangdong，China
Published: 2024-02-20 doi: 10.19457/j.1001-2095.dqcd24637
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The safe and efficient operation of lithium batteries depends on accurate state of charge （SOC） estimation. However，the traditional battery model and SOC estimation have poor robustness and reliability under noise interference. Aiming at the problem of SOC cooperative estimation under noise interference，firstly，the maximum available capacity and open circuit voltage （OCV） characteristics of the battery were analyzed，and the curve characteristics of lithium battery SOC—OCV were studied. Then，the problem of online model parameter identification and SOC estimation under noise interference was studied，and a two-swarm cooperative particle swarm optimization （TCPSO） method based on adaptive dynamic sliding window was proposed. Experimental results show that the maximum SOC estimation error of the proposed method is less than 1%，which shows that the proposed method can realize online parameter identification，and it is superior to the existing collaborative estimation methods in terms of anti-noise performance and SOC estimation accuracy.

state of charge （SOC） estimation  /  noise interference  /  parameter identification  /  two-swarm cooperative particle swarm optimization （TCPSO）
Ye ZHU, Yuanrui CHEN, Yang CHEN, Zhenlin WANG. Parameter Identification and SOC Estimation of Lithium Battery Based on Adaptive Dynamic Sliding Window[J]. Electric Drive, 2024 , 54 (2) : 12 -20 . DOI: 10.19457/j.1001-2095.dqcd24637
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Year 2024 volume 54 Issue 2
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Article Info
doi: 10.19457/j.1001-2095.dqcd24637
  • Receive Date：2022-09-23
  • Online Date：2026-01-13
  • Published：2024-02-20
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  • Received：2022-09-23
  • Revised：2022-11-02
Funding
Affiliations
    1 School of Electric Power，South China University of Technology，Guangzhou 510641，Guangdong，China
    2 School of Intelligent Science and Engineering，Harbin Engineering University，Harbin 150000，Heilongjiang，China
    3 School of Electronic Engineering，South China Agricultural University，Guangzhou 510642，Guangdong，China
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