|
|
|||
|
||||
OverviewGiven the limitations of state-of-the-art methods, this book presents a state of health (SOH) forecasting method that is suitable for lithium-ion battery (LIB) systems in real-world battery electric vehicle operation. Its histogram-based features can capture the higher operational variability compared to constant and controlled laboratory operation. Also, the transferability of a trained machine learning model to new LIB cell types and new operational domains is investigated. The presented SOH forecasting method can be provided as a cloud service via a web or smartphone app to fleet managers. Forecasting the SOH enables fleet managers of battery electric vehicle fleets to forecast and plan vehicle replacements. Full Product DetailsAuthor: Friedrich von BülowPublisher: Springer Fachmedien Wiesbaden Imprint: Springer Vieweg Edition: 1st ed. 2024 Volume: 170 Weight: 0.344kg ISBN: 9783658431877ISBN 10: 3658431873 Pages: 227 Publication Date: 02 February 2024 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand We will order this item for you from a manufactured on demand supplier. Table of ContentsReviewsAuthor InformationFriedrich von Bülow studied mechanical engineering and automation engineering at RWTH Aachen University. He completed his doctoral thesis at the Institute for Technologies and Management of Digital Transformation (TMDT) at the University of Wuppertal (BUW) while working in the automotive industry as a data scientist with a special interest in the analysis of time series data and applications of machine learning. Tab Content 6Author Website:Countries AvailableAll regions |