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

By Remus Teodorescu

Artificial Intelligence-Based State-of-Health Estimation of Lithium-Ion Batteries Business & Technology

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

0 - Default Title
Description
Lithium-ion batteries have a wide range of applications, but one of their biggest problems is their limited lifetime, which is 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. Therefore, this Special Issue showcase manuscripts showing efficient SOH estimation methods using AI which exhibit good performance, such as high accuracy, high robustness against the changes in working conditions, good generalization, etc.
Product details
Number of Pages:
184
Release Date:
2025-12-29
Publication Date:
2025-12-29
Publisher:
MDPI AG
Languages:
Original: English
ISBN10:
3725861870
ISBN13:
9783725861873
GPSR Manufacturer Reference:
[email protected]
Weight:
660 g
Height:
175 cm
Width:
250 cm
Thickness:
17 cm
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