Free Delivery Over $100
|
|
|||
|
||||
OverviewThis 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. Full Product DetailsAuthor: Remus Teodorescu , Xin SuiPublisher: Mdpi AG Imprint: Mdpi AG Dimensions: Width: 17.00cm , Height: 2.10cm , Length: 24.40cm Weight: 0.744kg ISBN: 9783036598758ISBN 10: 3036598758 Pages: 252 Publication Date: 27 February 2024 Audience: General/trade , General Format: Hardback Publisher's Status: Active Availability: In stock  We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately. Table of ContentsReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |
||||
