A Method for Estimating State of Health of Retired Lithium Battery

WANG Siliang; WU Xiaolan; BAI Zhifeng

doi:10.13433/j.cnki.1003-8728.20200576

Volume 42 Issue 1

Jan. 2023

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Article Navigation > Mechanical Science and Technology for Aerospace Engineering > 2023 > 42(1): 139-148

WANG Siliang, WU Xiaolan, BAI Zhifeng. A Method for Estimating State of Health of Retired Lithium Battery[J]. Mechanical Science and Technology for Aerospace Engineering, 2023, 42(1): 139-148. doi: 10.13433/j.cnki.1003-8728.20200576

Citation:

WANG Siliang, WU Xiaolan, BAI Zhifeng. A Method for Estimating State of Health of Retired Lithium Battery[J]. Mechanical Science and Technology for Aerospace Engineering, 2023, 42(1): 139-148. doi: 10.13433/j.cnki.1003-8728.20200576

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A Method for Estimating State of Health of Retired Lithium Battery

doi: 10.13433/j.cnki.1003-8728.20200576

WANG Siliang^{1, 2
,},
WU Xiaolan^{1, 2},
BAI Zhifeng^{1, 3
,
,}

1.
School of Mechanical and Electrical Engneering, Xi′an University of Architecture and Technology, Xi′an 710055, China
2.
Shaanxi Key Laboratory of Nanomaterials and Nanotechnology, Xi′an 710055, China
3.
Xi′an Key Laboratory of Clean Energy, Xi′an 710055, China

Received Date: 2021-02-14
Publish Date: 2023-01-25

Abstract

Abstract

Because the efficiency for estimating the state of health (SOH) of a retired lithium battery is low, a fast and efficient estimation method is proposed. Firstly, the third-order RC equivalent circuit model is used to describe the characteristics and obtain the state equation in order to ensure the accuracy of the battery model. At the same time, the state of charge (SOC) and ohmic internal resistance (R₀) are introduced as the parameters of the state equation. Secondly, the region concept was used to calculate the specific region capacity and region voltage so as to reduce the data and time needed for battery parameter estimation. The battery parameters SOC and R₀ were estimated with the extended Kalman filtering (EKF) algorithm, and then the SOH of the battery was estimated. Finally, a battery test device (Arbin-BT2000) was used to conduct charging and discharging experiments on the 18650 battery to verify the feasibility of the method proposed in the paper. The experimental results show that the parameters required for SOH estimation are significantly reduced, that the time required for battery data measurement is significantly shortened and that the estimation error with the method is less than 4%, indicating that the method can quickly and effectively estimate the SOH of the lithium battery.
- third-order RC equivalent circuit model,
- region capacity,
- region voltage,
- extended Kalman filtering algorithm

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References(20)

References

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