EconPapers    
Economics at your fingertips  
 

Data–Driven Fault Diagnosis and Cause Analysis of Battery Pack with Real Data

Jian Yang, Jaewook Jung, Samira Ghorbanpour and Sekyung Han
Additional contact information
Jian Yang: School of Electronic and Electrical Engineering, Kyungpook National University, Daegu 41566, Korea
Jaewook Jung: Department of Hydrogen and Renewable Energy, Kyungpook National University, Daegu 41566, Korea
Samira Ghorbanpour: School of Electronic and Electrical Engineering, Kyungpook National University, Daegu 41566, Korea
Sekyung Han: Department of Electrical Engineering, Kyungpook National University, Daegu 41566, Korea

Energies, 2022, vol. 15, issue 5, 1-19

Abstract: Owing to the increasing use of electric vehicles (EVs), the demand for lithium-ion (Li-ion) batteries is rising. In this light, an essential factor governing the safety and efficiency of electric vehicles is the proper diagnosis of battery errors. In this article, we address the detection of battery problems by using the intraclass correlation coefficient (ICC) method and the order of cell voltages to enhance EV performance. Furthermore, we propose a framework for diagnosing problems with battery packs, which could be used to detect abnormal behavior. The proposed method calculates ICC values based on the terminal voltages extracted from a caravan battery pack. These ICC values are then used to determine whether the battery has a defect. In addition, the order of cell voltages is used to analyze the causes of faults. Furthermore, we conducted experiments to investigate and evaluate battery cell faults in EVs. The experimental results indicate that the proposed approach can be used to detect battery cell faults accurately.

Keywords: battery management system (BMS); fault diagnosis; LFP battery; electric vehicle; correlation coefficient (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1996-1073/15/5/1647/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/5/1647/ (text/html)

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:gam:jeners:v:15:y:2022:i:5:p:1647-:d:756296

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-03-19
Handle: RePEc:gam:jeners:v:15:y:2022:i:5:p:1647-:d:756296