Fractional Order Intelligent Modeling for Lithium-Ion Batteries

Theory and Practice
1. Auflage 2025
ISBN: 978-1-041-13269-1
Verlag: CRC Press

Buch, Englisch, 160 Seiten, Format (B × H): 178 mm x 254 mm

Reihe: Fractional Order Thinking in Exploring the Frontiers of STEM

This book focuses on fractional order (non-integer order) modeling (FOM) techniques coupled with deep neural network-based intelligent modeling methods for lithium-ion batteries (LIBs) and battery management systems (BMS) in general. It provides the first one-stop resource on FOM for LIBs with case studies using real operational data sets.

With the rapid growth of electric vehicles and energy storage systems, battery technology has become critical to global energy solutions. This book aims to provide several accurate and effective intelligent modeling algorithms for the next generation of advanced BMS. Key topics include intelligent battery modeling, fractional-order modeling, physics-informed machine learning, state estimation, and degradation analysis. By integrating AI and physics-informed machine learning techniques with fractional-order modeling methods, this book presents several innovative solutions for next-generation battery management systems.

This title will serve as an invaluable resource for researchers and advanced students in the fields of transportation, energy storage, and power systems, as well as those studying electric vehicles, control theory, machine learning, and fractional calculus-based modeling.

Zielgruppe

Academic, Postgraduate, Professional Practice & Development, Professional Reference, Undergraduate Advanced, and Undergraduate Core

Autoren/Hrsg.

Wang, Yanan

Chen, Yangquan

Fachgebiete

• Mathematik | Informatik Mathematik Mathematische Analysis
• Technische Wissenschaften Energietechnik | Elektrotechnik Alternative und erneuerbare Energien
• Naturwissenschaften Physik Mechanik Energie
• Technische Wissenschaften Energietechnik | Elektrotechnik Energieverteilung, Stromnetze
• Technische Wissenschaften Energietechnik | Elektrotechnik Elektrotechnik

Inhaltsverzeichnis

1. Introduction 2. A Review on Fractional-Order Modeling 3. Fractional-order Algorithms for Battery State Estimation 4. Fractional-order Algorithms for Battery Capacity Estimation 5. Intelligent Modeling with Smart Sensors for Battery 6. Perspectives on Intelligent Fractional-Order Modeling 7. Conclusions and Take-home Messages

Über Autor(innen)

YaNan Wang is currently an assistant professor and a member of Low-carbon Powertrain Systems Research Lab at Beijing University of Technology, China. Her research focuses on AI-driven battery intelligent management and safety evaluation for power batteries, addressing critical issues such as fast degradation and fault diagnosis.

YangQuan Chen is a professor at the University of California Merced, US. His research interests include mechatronics for sustainability, digital twins, small multi-UAV, applied fractional calculus. His recent publication with CRC Press includes Fractional Calculus for Skeptics I: The Fractal Paradigm.