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Data Science-Based Full-Lifespan Management of Lithium-Ion Battery
Details
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.
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
Inhalt
Chapter 1. Introduction to Battery Full-Lifespan Management.- Chapter 2. Key Stages for Battery Full-Lifespan Management.- Chapter 3. Data Science-based Battery Manufacturing Management.- Chapter 4. Data Science-based Battery Operation Management I.- Chapter 5. Data Science-based Battery Operation Management II.- Chapter 6. Data Science-based Battery Reutilization Management.- Chapter 7. The Ways Ahead.
Weitere Informationen
- Allgemeine Informationen
- GTIN 09783031013393
- Lesemotiv Verstehen
- Genre Mechanical Engineering
- Auflage 1st edition 2022
- Sprache Englisch
- Anzahl Seiten 284
- Herausgeber Springer International Publishing
- Größe H241mm x B160mm x T21mm
- Jahr 2022
- EAN 9783031013393
- Format Fester Einband
- ISBN 3031013395
- Veröffentlichung 10.04.2022
- Titel Data Science-Based Full-Lifespan Management of Lithium-Ion Battery
- Autor Kailong Liu , Xin Lai , Yujie Wang
- Untertitel Manufacturing, Operation and Reutilization
- Gewicht 594g