Science, Nature & Maths      Chemistry

Artificial Intelligence-Based State-of-Health Estimation of Lithium-Ion Batteries

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Book Details
Language
English
Publishers
MDPI AG (27 Feb. 2024)
Weight
0.74 KG
Publication Date
27/02/2024
ISBN-10
3036598758
Pages
252 pages
ISBN-13
9783036598758
Dimensions
16.99 x 2.06 x 24.41 cm
SKU
9783036598758
Author Name
Remus Teodorescu (Editor)
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This reprint aims to showcase manuscripts presenting efficient SOH estimation methods using AI which exhibit good performance such as high accuracy, high robustness against the changes in working conditions, and good generalization, etc. Lithium-ion batteries have a wide range of applications, but one of their biggest problems is their limited lifetime due to performance degradation during usage.

It is, therefore, essential to determine the battery's state of health (SOH) so that the battery management system can control the battery, enabling it to run in the best state and thus prolonging its lifetime. Artificial intelligence (AI) technologies possess immense potential in inferring battery SOH and can extract aging information (i.

e. , SOH features) from measurements and relate them to battery performance parameters, avoiding a complex battery modeling process.

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