EconPapers    
Economics at your fingertips  
 

Multi-objective nonlinear observer design for multi-fault detection of lithium-ion battery in electric vehicles

Yiming Xu, Xiaohua Ge and Weixiang Shen

Applied Energy, 2024, vol. 362, issue C, No S0306261924003726

Abstract: Accurate and rapid fault detection is essential for the safe operation of lithium-ion batteries in electric vehicles. However, conventional fault detection methods dependent on constant thresholds may have false alarms or missing alarms due to the inevitable disturbances resulted from the battery system modeling errors and measurement noises. In this paper, we design a multi-objective nonlinear fault detection observer for lithium-ion batteries, which is robust against disturbances but sensitive to battery multi-fault. We then perform formal stability and L∞/H_ performance analysis for the resultant estimation error system. Furthermore, tractable design procedures for the observer gain parameter and an adaptive threshold are derived. Then, via adaptive thresholding, a delicate three-step multi-fault detection scheme is developed to detect the occurrence of battery various faults, including short-circuit faults, current and voltage sensor faults. Finally, the efficacy of the proposed scheme is validated under several experimental case studies involving a variety of faults with their different levels of severity and erroneous SOC initialization.

Keywords: Lithium-ion battery; Electric vehicle; Multi-objective observer; Adaptive threshold; Multi-fault detection; Sensor fault; Internal short circuit (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261924003726
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:362:y:2024:i:c:s0306261924003726

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic

DOI: 10.1016/j.apenergy.2024.122989

Access Statistics for this article

Applied Energy is currently edited by J. Yan

More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu (repec@elsevier.com).

 
Page updated 2024-12-28
Handle: RePEc:eee:appene:v:362:y:2024:i:c:s0306261924003726