Data Science-Based Full-Lifespan Management of Lithium-Ion Battery : Manufacturing, Operation and Reutilization / / Kailong Liu, Yujie Wang, Xin Lai

• Autore: Liu Kailong
• Pubblicazione: Cham, : Springer International Publishing AG, 2022; ©2022
• Descrizione fisica: 1 online resource (277 p.) : illustrations (chiefly color)
• Soggetto topico: Battery management systems; Lithium ion batteries
• Soggetto non controllato: Lithium-ion Battery; Battery Manufacturing Management; Battery Operation Management; Battery Recycling Management; Data Science; Artificial Intelligence; Open Access
• Altri autori: WangYujie LaiXin
• Note generali: Description based upon print version of record.
• Nota di contenuto: 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.
• Sommario/riassunto: 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.
• Titolo autorizzato: Data Science-Based Full-Lifespan Management of Lithium-Ion Battery
• ISBN: 3-031-01340-9
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910558694203321
• Lo trovi qui: Univ. Federico II
• Serie: Green Energy and Technology.