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Estimation of State-of-health of Lithium-ion Batteries Based on ISSA-GPR
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Mengdi ZHANG1, Yang LIU1, Jian CHEN2, Jinpeng JI1, Zhiwei YAO1, Yanyong GONG1
Journal of Power Supply | 2026, 24(2) : 233 - 243
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Journal of Power Supply | 2026, 24(2): 233-243
• AI and Power Electronics •
Estimation of State-of-health of Lithium-ion Batteries Based on ISSA-GPR
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Mengdi ZHANG1, Yang LIU1, Jian CHEN2, Jinpeng JI1, Zhiwei YAO1, Yanyong GONG1
Affiliations
  • 1.School of Electrical and Electronic Engineering, Shandong University of Technology, Zibo 255049, China
  • 2.Zibo Institute of Measurement Technology, Zibo 255025, China
Published: 2026-02-28 doi: 10.13234/j.issn.2095-2805.2026.2.233
Outline
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The state-of-health (SOH) of a battery is difficult to be directly measured, so an accurate estimation of SOH is critical for ensuring its safe operation. Aimed at the problem of SOH estimation of lithium-ion batteries, an SOH estimation method based on improved sparrow search algorithm-Gaussian process regression (ISSA-GPR) is proposed. First, ISSA is used to optimize the parameters of a GPR model, and the GPR model based on ISSA is constructed. Then, the capacity increment curve is analyzed to extract the health factors that characterize the battery capacity degradation as the input of the model, the optimal voltage interval length with the peak as the center area is determined by ISSA, and the SOH of batteries is obtained to perform estimation. Finally, the public experimental data sets are applied to verify the proposed method. Experimental results show that the proposed ISSA-GPR method can accurately estimate the SOH of batteries.

Lithium-ion battery  /  state-of-health (SOH)  /  capacity increment curve  /  health factor  /  sparrow search algorithm  /  Gaussian process regression (GPR)
张梦迪, 刘洋, 陈健, 吉金鹏, 姚智伟, 公衍勇. 基于ISSA-GPR的锂离子电池健康状态估计. 电源学报, 2026 , 24 (2) : 233 -243 . DOI: 10.13234/j.issn.2095-2805.2026.2.233
Mengdi ZHANG, Yang LIU, Jian CHEN, Jinpeng JI, Zhiwei YAO, Yanyong GONG. Estimation of State-of-health of Lithium-ion Batteries Based on ISSA-GPR[J]. Journal of Power Supply, 2026 , 24 (2) : 233 -243 . DOI: 10.13234/j.issn.2095-2805.2026.2.233
Funding
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  • National Key R&D Program of China(2017YFB0902800)
  • Shandong Province Postgraduate Education and Teaching Reform Research Project(SDYJG19103)
  • Science and Technology Project of State Grid Corporation of China(52094017003D)
Appendix
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Year 2026 volume 24 Issue 2
33
4
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Article Info
doi: 10.13234/j.issn.2095-2805.2026.2.233
  • Receive Date：2023-07-11
  • Online Date：2026-10-29
  • Published：2026-02-28
Article Data
Affiliations
History
  • Received：2023-07-11
  • Revised：2023-09-12
  • Accepted：2023-10-13
Funding
National Key R&D Program of China(2017YFB0902800)
Shandong Province Postgraduate Education and Teaching Reform Research Project(SDYJG19103)
Science and Technology Project of State Grid Corporation of China(52094017003D)
Affiliations
    1.School of Electrical and Electronic Engineering, Shandong University of Technology, Zibo 255049, China
    2.Zibo Institute of Measurement Technology, Zibo 255025, China
References
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https://castjournals.cast.org.cn/joweb/dyxb/EN/10.13234/j.issn.2095-2805.2026.2.233
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表12种不同金属材料的力学参数
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小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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