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6 August 2023 Fault diagnosis of power battery based on temperature probe ranking entropy
Zhaosheng Zhang, Zhiwei Sun, Ximing Cheng, Zhang Zhang
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Proceedings Volume 12781, International Conference on Optoelectronic Information and Functional Materials (OIFM 2023); 127810K (2023) https://doi.org/10.1117/12.2686738
Event: 2023 International Conference on Optoelectronic Information and Functional Materials (OIFM 2023), 2023, Guangzhou, JS, China
Abstract
Aiming at the problems of large computational complexity and poor timeliness in electric vehicle battery fault diagnosis, a method for power battery fault diagnosis based on temperature data during parking charging phase was studied. Calculate the temperature probe ordering matrix for each charging segment, select the sliding window length k=50, step length b=1, and calculate the coefficient of variation of the probe ordering entropy within each sliding window. Set the alarm threshold to 3 to give an abnormal temperature change alarm to the probe. By analyzing the temperature probe data at the time of a vehicle thermal runaway accident, the accuracy and timeliness of the early warning method are verified, providing a new idea for power battery fault diagnosis.
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Zhaosheng Zhang, Zhiwei Sun, Ximing Cheng, and Zhang Zhang "Fault diagnosis of power battery based on temperature probe ranking entropy", Proc. SPIE 12781, International Conference on Optoelectronic Information and Functional Materials (OIFM 2023), 127810K (6 August 2023); https://doi.org/10.1117/12.2686738
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KEYWORDS
Batteries
Data modeling
Data transmission
Data acquisition
Data processing
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