Citation

Jaime-Barquero E, Bekaert E, Olarte J, Zulueta E, Lopez-Guede JM. Batteries (Basel) 2023; 9(7): e388.

Copyright

(Copyright © 2023, MDPI: Multidisciplinary Digital Publications Institute)

DOI

10.3390/batteries9070388

PMID

unavailable

Abstract

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.

Language: en

Keywords

degradation mechanism; Li-ion battery; modelling; neural network; safety