Artificial Intelligence Opportunities to Diagnose Degradation Modes for Safety Operation in Lithium Batteries

The degradation and safety study of lithium-ion batteries is becoming increasingly important given that these batteries are widely used not only in electronic devices but also in automotive vehicles. Consequently, the detection of degradation modes that could lead to safety alerts is essential. Exis...

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Bibliographic Details
Main Authors: Edurne Jaime-Barquero, Emilie Bekaert, Javier Olarte, Ekaitz Zulueta, Jose Manuel Lopez-Guede
Format: Article
Language:English
Published: MDPI AG 2023-07-01
Series:Batteries
Subjects:
Online Access:https://www.mdpi.com/2313-0105/9/7/388
Description
Summary:The degradation and safety study of lithium-ion batteries is becoming increasingly important given that these batteries are widely used not only in electronic devices but also in automotive vehicles. Consequently, the detection of degradation modes that could lead to safety alerts is essential. Existing methodologies are diverse, experimental based, model based, and the new trends of artificial intelligence. This review aims to analyze the existing methodologies and compare them, opening the spectrum to those based on artificial intelligence (AI). AI-based studies are increasing in number and have a wide variety of applications, but no classification, in-depth analysis, or comparison with existing methodologies is yet available.
ISSN:2313-0105