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Data Science-Based Full-Lifespan Management of Lithium-Ion Battery
Kailong Liu, Yujie Wang, Xin Lai
2022
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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.
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Keywords
- artificial intelligence
- Battery Manufacturing Management
- Battery Operation Management
- Battery Recycling Management
- Computing & information technology
- Data science
- Databases
- Energy technology & engineering
- lithium-ion battery
- Materials science
- Mechanical engineering & materials
- open access
- Technology, engineering, agriculture
- thema EDItEUR::U Computing and Information Technology::UN Databases
Links
DOI: 10.1007/978-3-031-01340-9Editions