A Combined Model-Based and Data-Driven Fault Diagnosis Scheme for Lithium-Ion Batteries-Reference-Cited by-同舟云学术

A Combined Model-Based and Data-Driven Fault Diagnosis Scheme for Lithium-Ion Batteries

Published:2024-06 Issue:6 Volume:71 Page:6274-6284
ISSN:0278-0046
Container-title:IEEE Transactions on Industrial Electronics
language:
Short-container-title:IEEE Trans. Ind. Electron.

Author:

Jin Hailang¹^ORCID,Gao Zhiwei²^ORCID,Zuo Zhiqiang¹^ORCID,Zhang Zhicheng¹^ORCID,Wang Yijing¹^ORCID,Zhang Aihua³^ORCID

Affiliation:

1. Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System, School of Electrical and Information Engineering, Tianjin University, Tianjin, China

2. Faculty of Engineering and Environment, University of Northumbria, Newcastle upon Tyne, U.K.

3. College of Physical Science and Technology, Bohai University, Jinzhou, China

Funder

National Natural Science Foundation of China

Tianjin Research Innovation Project for Postgraduate Students

Alexander von Humboldt-Stiftung

China Scholarship Council

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/41/10416960/10203013.pdf?arnumber=10203013

Reference38 articles.

1. Data-driven prediction of battery cycle life before capacity degradation

2. Online Fault Diagnosis of External Short Circuit for Lithium-Ion Battery Pack

3. A Neural Network Based Method for Thermal Fault Detection in Lithium-Ion Batteries

4. A Sensor Fault Diagnosis Method for a Lithium-Ion Battery Pack in Electric Vehicles

5. A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches

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