LAPSE:2023.2244
Published Article

LAPSE:2023.2244
A Review of Lithium-Ion Battery Thermal Runaway Modeling and Diagnosis Approaches
February 21, 2023
Abstract
Lithium-ion (Li-ion) batteries have been utilized increasingly in recent years in various applications, such as electric vehicles (EVs), electronics, and large energy storage systems due to their long lifespan, high energy density, and high-power density, among other qualities. However, there can be faults that occur internally or externally that affect battery performance which can potentially lead to serious safety concerns, such as thermal runaway. Thermal runaway is a major challenge in the Li-ion battery field due to its uncontrollable and irreversible nature, which can lead to fires and explosions, threatening the safety of the public. Therefore, thermal runaway prognosis and diagnosis are significant topics of research. To efficiently study and develop thermal runaway prognosis and diagnosis algorithms, thermal runaway modeling is also important. Li-ion battery thermal runaway modeling, prediction, and detection can help in the development of prevention and mitigation approaches to ensure the safety of the battery system. This paper provides a comprehensive review of Li-ion battery thermal runaway modeling. Various prognostic and diagnostic approaches for thermal runaway are also discussed.
Lithium-ion (Li-ion) batteries have been utilized increasingly in recent years in various applications, such as electric vehicles (EVs), electronics, and large energy storage systems due to their long lifespan, high energy density, and high-power density, among other qualities. However, there can be faults that occur internally or externally that affect battery performance which can potentially lead to serious safety concerns, such as thermal runaway. Thermal runaway is a major challenge in the Li-ion battery field due to its uncontrollable and irreversible nature, which can lead to fires and explosions, threatening the safety of the public. Therefore, thermal runaway prognosis and diagnosis are significant topics of research. To efficiently study and develop thermal runaway prognosis and diagnosis algorithms, thermal runaway modeling is also important. Li-ion battery thermal runaway modeling, prediction, and detection can help in the development of prevention and mitigation approaches to ensure the safety of the battery system. This paper provides a comprehensive review of Li-ion battery thermal runaway modeling. Various prognostic and diagnostic approaches for thermal runaway are also discussed.
Record ID
Keywords
battery modeling, fault diagnosis, internal short-circuit, lithium-ion battery, thermal runaway
Subject
Suggested Citation
Tran MK, Mevawalla A, Aziz A, Panchal S, Xie Y, Fowler M. A Review of Lithium-Ion Battery Thermal Runaway Modeling and Diagnosis Approaches. (2023). LAPSE:2023.2244
Author Affiliations
Tran MK: Department of Chemical Engineering, University of Waterloo, 200 University Avenue West, Waterloo, ON N2L 3G1, Canada [ORCID]
Mevawalla A: Department of Chemical Engineering, University of Waterloo, 200 University Avenue West, Waterloo, ON N2L 3G1, Canada
Aziz A: Department of Chemical Engineering, University of Waterloo, 200 University Avenue West, Waterloo, ON N2L 3G1, Canada
Panchal S: Department of Mechanical and Mechatronics Engineering, University of Waterloo, 200 University Avenue West, Waterloo, ON N2L 3G1, Canada [ORCID]
Xie Y: College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044, China [ORCID]
Fowler M: Department of Chemical Engineering, University of Waterloo, 200 University Avenue West, Waterloo, ON N2L 3G1, Canada [ORCID]
Mevawalla A: Department of Chemical Engineering, University of Waterloo, 200 University Avenue West, Waterloo, ON N2L 3G1, Canada
Aziz A: Department of Chemical Engineering, University of Waterloo, 200 University Avenue West, Waterloo, ON N2L 3G1, Canada
Panchal S: Department of Mechanical and Mechatronics Engineering, University of Waterloo, 200 University Avenue West, Waterloo, ON N2L 3G1, Canada [ORCID]
Xie Y: College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044, China [ORCID]
Fowler M: Department of Chemical Engineering, University of Waterloo, 200 University Avenue West, Waterloo, ON N2L 3G1, Canada [ORCID]
Journal Name
Processes
Volume
10
Issue
6
First Page
1192
Year
2022
Publication Date
2022-06-15
ISSN
2227-9717
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Original Submission
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PII: pr10061192, Publication Type: Review
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LAPSE:2023.2244
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https://doi.org/10.3390/pr10061192
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Feb 21, 2023
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