A Fast Diagnosis Method for Internal Short Circuit Fault in Energy Storage Batteries Based on Electrochemical Impedance Spectroscopy

Internal short circuits are common extreme battery faults. Due to the unclear characteristics of external voltage changes, early diagnosis of internal short circuit faults has received widespread attention. To address the issue of early warning, this paper proposes a fast diagnostic method for internal short circuit faults in batteries based on electrochemical impedance spectroscopy (EIS). Firstly, by applying pulse current excitation to the battery, the voltage response results of the battery are collected, combined with wavelet transform to obtain the EIS of the battery in multiple frequency bands. Based on this, Nyquist plots are drawn to compare batteries with different simulated short-circuit levels, and the trend of curve changes are observed. Then, a battery internal short circuit fault diagnosis experimental testing platform was built to verify this method. The results showed that the fast calculation method based on pulse current excitation and response can accurately obtain AC impedance of 0.1Hz-10Hz, with a root mean square error of 0.44m Ω in the real part and 0.22m Ω in the imaginary part. The fast acquisition method of battery impedance spectrum can effectively diagnose internal short circuit. Diagnose internal short circuit faults and their severity based on the slope of the Nyquist plot line and the offset of the intersection point between the line and the semi-circular part. This method can be used for daily fault diagnosis, which is beneficial for ensuring the safety of residential battery use.

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Published
2024-10-25
DOI
https://doi.org/10.1109/icsgsc62639.2024.10813917
Primary Topic
Power Systems and Renewable Energy
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article
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article

A Fast Diagnosis Method for Internal Short Circuit Fault in Energy Storage Batteries Based on Electrochemical Impedance Spectroscopy

WU Da-wei, Cuixiang Xu, Jinlei Sun, Xin Li et al.
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Power Systems and Renewable Energy
article

A Fast Diagnosis Method for Internal Short Circuit Fault in Energy Storage Batteries Based on Electrochemical Impedance Spectroscopy

WU Da-wei, Cuixiang Xu, Jinlei Sun, Xin Li, Pengfei Li, Siwen Chen
article en

Abstract

Internal short circuits are common extreme battery faults. Due to the unclear characteristics of external voltage changes, early diagnosis of internal short circuit faults has received widespread attention. To address the issue of early warning, this paper proposes a fast diagnostic method for internal short circuit faults in batteries based on electrochemical impedance spectroscopy (EIS). Firstly, by applying pulse current excitation to the battery, the voltage response results of the battery are collected, combined with wavelet transform to obtain the EIS of the battery in multiple frequency bands. Based on this, Nyquist plots are drawn to compare batteries with different simulated short-circuit levels, and the trend of curve changes are observed. Then, a battery internal short circuit fault diagnosis experimental testing platform was built to verify this method. The results showed that the fast calculation method based on pulse current excitation and response can accurately obtain AC impedance of 0.1Hz-10Hz, with a root mean square error of 0.44m Ω in the real part and 0.22m Ω in the imaginary part. The fast acquisition method of battery impedance spectrum can effectively diagnose internal short circuit. Diagnose internal short circuit faults and their severity based on the slope of the Nyquist plot line and the offset of the intersection point between the line and the semi-circular part. This method can be used for daily fault diagnosis, which is beneficial for ensuring the safety of residential battery use.

Nanjing University of Science and Technology (CN), NARI Group (China) (CN)
Affordable and clean energy
Openalex Percentile: Top 73%
Power Systems and Renewable Energy
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A Fast Diagnosis Method for Internal Short Circuit Fault in Energy Storage Batteries Based on Electrochemical Impedance Spectroscopy — WU Da-wei, Cuixiang Xu, et al. · (2024) | TGRS Research Map | TGRS