Home Journals Articles Updates About
CN
image
收藏切换
Battery Fault Diagnosis for Electric Vehicle Based on the Kalman Filter and Feature-Exponential-Function Method
收藏切换
PDF
Minghu Wu1, 2, Wanyin Du1, Fan Zhang1, Wei Huang1
Automobile Technology | 2023, (8) : 7 - 13
Less
收藏切换
Automobile Technology | 2023, (8): 7-13
• ※ Special Topic on Safety Technologies of Lithium-Ion Batteries for Electric Vehicles •
Battery Fault Diagnosis for Electric Vehicle Based on the Kalman Filter and Feature-Exponential-Function Method
Full
Minghu Wu1, 2, Wanyin Du1, Fan Zhang1, Wei Huang1
Affiliations
  • 1 Hubei Key Laboratory for High-Efficiency Utilization of Solar Energy and Operation Control of Energy Storage System, Hubei University of Technology, Wuhan 430068
  • 2 Hubei Engineering Research Center for Safety Monitoring of New Energy and Power Grid Equipment, Hubei University of Technology, Wuhan 430068
Published: 2023-08-24 doi: 10.19620/j.cnki.1000-3703.20220891
Outline
收藏切换

A battery fault online diagnosis method based on Kalman filtering and feature indexing was proposed for the faults such as thermal runaway and internal short circuit in the battery pack. Firstly, data noise reduction was performed based on historical data and Kalman filtering method to effectively remove voltage anomalies and a feature indexing method was proposed to extract and amplify the voltage characteristics between battery pack cells. Finally, a fault value calculation method based on cosine similarity was proposed in order to reduce the false alarm due to battery pack inconsistency and to automatically detect and locate the faulty battery online. Verification in cloud-based vehicle data shows that the proposed battery fault diagnosis algorithm based on Kalman filtering and feature indexing can effectively detect faulty batteries and provide early warning.

Lithium ion battery  /  Fault diagnosis  /  Kalman filter  /  Feature extraction  /  Cosine similarity
Minghu Wu, Wanyin Du, Fan Zhang, Wei Huang. Battery Fault Diagnosis for Electric Vehicle Based on the Kalman Filter and Feature-Exponential-Function Method[J]. Automobile Technology, 2023 , (8) : 7 -13 . DOI: 10.19620/j.cnki.1000-3703.20220891
Appendix
Less
Year 2023 volume Issue 8
PDF
249
111
Cite this Article
BibTeX
Article Info
doi: 10.19620/j.cnki.1000-3703.20220891
  • Online Date：2025-12-07
  • Published：2023-08-24
Article Data
Affiliations
History
  • Revised：2022-11-06
Funding
Affiliations
    1 Hubei Key Laboratory for High-Efficiency Utilization of Solar Energy and Operation Control of Energy Storage System, Hubei University of Technology, Wuhan 430068
    2 Hubei Engineering Research Center for Safety Monitoring of New Energy and Power Grid Equipment, Hubei University of Technology, Wuhan 430068
References
Share
https://castjournals.cast.org.cn/joweb/qcjs/EN/10.19620/j.cnki.1000-3703.20220891
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT
Links
Articles
Latest Articles
Most Read
Collections
Updates
Events
News
Multimedia
About
About Us
Contact
No. 86 Xueyuan South Road, Haidian District, Beijing
100081
010-62199257
qkjq@cast.org.cn

Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House