A Data-Driven Fleet Service: State of Health Forecasting of Lithium-Ion Batteries

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Friedrich von Bülow

A Data-Driven Fleet Service

State of Health Forecasting of Lithium-Ion Batteries

Friedrich von Bülow

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English

Springer Vieweg
02 February 2024

Manufacturing industries; Electrical engineering; Power generation & distribution; Energy conversion & storage; Automotive technology & trades

Series: AutoUni – Schriftenreihe

Given 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.

By: Friedrich von Bülow
Imprint: Springer Vieweg
Country of Publication: Germany
Edition: 1st ed. 2024
Volume: 170
Dimensions: Height: 210mm, Width: 148mm,
Weight: 344g
ISBN: 9783658431877
ISBN 10: 3658431873
Series: AutoUni – Schriftenreihe
Pages: 227
Publication Date: 02 February 2024
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

Friedrich 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.