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A Review of Lithium-Ion Battery Thermal Runaway Modeling and Diagnosis Approaches

A review connecting thermal-runaway model choices with prediction and detection methods; background for understanding what a numerical verification case can and cannot establish.

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Source descriptionSource record reviewed

Paper at a glance

PublicationDetails
AuthorsManh-Kien Tran, Anosh Mevawalla, Attar Aziz, Satyam Panchal, Yi Xie and Michael Fowler
JournalProcesses 10(6), article 1192
Published15 June 2022
DOI10.3390/pr10061192
Reading scopeAbstract and Sections 3–4 reviewed on 10 October 2026

What the review covers

This review surveys thermal-runaway models and approaches to prediction and detection. Section 3 discusses model fidelity, heat generation, thermal transport and experimental comparisons. Section 4 distinguishes prediction before an event from detection during it. The reviewed models span different cell formats, abuse conditions and physical mechanisms. Read the publisher’s article.

Connection to Lemonergy

Begin with thermal propagation verification. Its examples isolate heat exchange between two thermal masses, a finite energy release and event propagation. Those small models make energy accounting and event behavior inspectable before a larger model is assembled.

The review provides context for deciding what a real-cell model must represent. It does not validate Lemonergy’s examples. The supplied verification cases use authored parameters and do not reproduce the review’s experiments or establish a specific cell’s runaway threshold.

Read with a modeling question

  1. State the question: temperature response, event timing, propagation, or detection.
  2. List the mechanisms your model includes and the ones it omits.
  3. Inspect the reduced-coupling comparison to see how changing one connection changes the authored scenario.
  4. Use the results guide to separate passing numerical checks from agreement with measured data.

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Reference details

Reference type
paper
Authors
Manh-Kien Tran; Anosh Mevawalla; Attar Aziz; Satyam Panchal; Yi Xie; Michael Fowler
Publisher
MDPI — Processes
Published
2022-06-15
DOI
10.3390/pr10061192
Source accessed
2026-10-10

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