A data-driven compact AI model for automatic detection of thermal anomalies in large-format pouch cells

EES batteries. 2026 Open access

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Authors: Danial Sarwar, Abd El Rahman Shabayek, Tazdin Amietszajew
DOI: 10.1039/d6eb00049e
Cited by: 0
References: 33

Abstract

Distributed thermal sensing and AI-driven anomaly detection provide an effective framework for early hotspot identification and enhanced safety of large-format lithium-ion batteries.

Fields of Study & Subjects

Battery Modeling and Management Advancements in Battery Materials Fault Detection and Control Systems

Publication details

Journal / source
EES batteries.
Volume
2
Issue
5
Pages
1678–1688
Publication date
1 January 2026
Language
EN