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Sliding mode-based H-infinity filter for SOC estimation of lithium-ion batteries

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Abstract

H-infinity filter (HIf) is widely used in state of charge (SOC) estimation of lithium-ion batteries due to its superior performance to extended Kalman filter (EKF) whose robustness is weak. In this paper, an improved HIf-based SOC estimation algorithm is proposed, which incorporates a sliding mode observer, yielding better estimation stability and accuracy than conventional HIf. The proposed algorithm takes advantages of HIf and sliding mode observer that it is more robust to the modeling error and noises. Samsung ICR18650 lithium-ion battery cell is tested and results show that the proposed method improves SOC estimation accuracy, two error indicators are evaluated and both are reduced compared to that of the EKF and HIf.

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Funding

This work was supported by Natural Science Foundation of Jangsu Province and the Natural Science Foundation of NJUPT under Grant NY220217.

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Authors and Affiliations

  1. School of Automation and Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing, 210023, China

    Jianxin Yao, Jie Ding, Yanyun Cheng & Liang Feng

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  1. Jianxin Yao
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  2. Jie Ding
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  3. Yanyun Cheng
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  4. Liang Feng
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Correspondence to Jie Ding.

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Yao, J., Ding, J., Cheng, Y. et al. Sliding mode-based H-infinity filter for SOC estimation of lithium-ion batteries. Ionics 27, 5147–5157 (2021). https://doi.org/10.1007/s11581-021-04234-3

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