@inproceedings{e6a58329273e4ee39525df606939acd1,
title = "Fault Diagnosis of Power Battery Based on Temperature Probe Ranking Entropy",
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.",
keywords = "battery, fault diagnosis, probe ordering entropy",
author = "Zhaosheng Zhang and Zhiwei Sun and Ximing Cheng and Zhang Zhang",
note = "Publisher Copyright: {\textcopyright} 2023 SPIE.; 2023 International Conference on Optoelectronic Information and Functional Materials, OIFM 2023 ; Conference date: 14-04-2023 Through 16-04-2023",
year = "2023",
doi = "10.1117/12.2686738",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Yabo Fu and Prakash, {Kolla Bhanu}",
booktitle = "International Conference on Optoelectronic Information and Functional Materials, OIFM 2023",
address = "United States",
}