Authors:
Provides an up-to-date summary of current expertise in battery management
Includes step-by-step instructions for practical battery management and real case studies
Consolidates studies in the rapidly emerging field of battery management
This book is open access, which means that you have free and unlimited access.
Part of the book series: Green Energy and Technology (GREEN)
Buying options
Table of contents (7 chapters)
-
Front Matter
About this book
This open access book comprehensively consolidates studies in the rapidly emerging field of battery management. The primary focus is to overview the new and emerging data science technologies for full-lifespan management of Li-ion batteries, which are categorized into three groups, namely (i) battery manufacturing management, (ii) battery operation management, and (iii) battery reutilization management. The key challenges, future trends as well as promising data-science technologies to further improve this research field are discussed. As battery full-lifespan (manufacturing, operation, and reutilization) management is a hot research topic in both energy and AI fields and none specific book has focused on systematically describing this particular from a data science perspective before, this book can attract the attention of academics, scientists, engineers, and practitioners. It is useful as a reference book for students and graduates working in related fields. Specifically, the audience could not only get the basics of battery manufacturing, operation, and reutilization but also the information of related data-science technologies. The step-by-step guidance, comprehensive introduction, and case studies to the topic make it accessible to audiences of different levels, from graduates to experienced engineers.
Keywords
- Lithium-ion Battery
- Battery Manufacturing Management
- Battery Operation Management
- Battery Recycling Management
- Data Science
- Artificial Intelligence
- Open Access
Authors and Affiliations
-
Warwick Manufacturing Group (WMG), University of Warwick, Coventry, UK
Kailong Liu
-
Department of Automation, University of Science and Technology of China, Hefei, China
Yujie Wang
-
School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai, China
Xin Lai
Bibliographic Information
Book Title: Data Science-Based Full-Lifespan Management of Lithium-Ion Battery
Book Subtitle: Manufacturing, Operation and Reutilization
Authors: Kailong Liu, Yujie Wang, Xin Lai
Series Title: Green Energy and Technology
DOI: https://doi.org/10.1007/978-3-031-01340-9
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s) 2022
License: CC BY
Hardcover ISBN: 978-3-031-01339-3Published: 10 April 2022
Softcover ISBN: 978-3-031-01342-3Published: 10 April 2022
eBook ISBN: 978-3-031-01340-9Published: 08 April 2022
Series ISSN: 1865-3529
Series E-ISSN: 1865-3537
Edition Number: 1
Number of Pages: XXIII, 258
Number of Illustrations: 5 b/w illustrations, 158 illustrations in colour
Topics: Batteries, Materials for Energy and Catalysis, Data Engineering, Electrical Power Engineering