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Autor(en): 
  • Xin Lai
  • Kailong Liu
  • Yujie Wang
  • Data Science-Based Full-Lifespan Management of Lithium-Ion Battery: Manufacturing, Operation and Reutilization 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 7-14 Tagen versandfertig
    Veröffentlichung:  April 2022  
    Genre:  Naturwissensch., Medizin, Technik 
     
    ArtificialIntelligence / BatteryManufacturingManagement / BatteryOperationManagement / BatteryRecyclingManagement / DataScience / Datenbanken / Datenmanagement / Elektrotechnik / lithium-ionbattery
    ISBN:  9783031013393 
    EAN-Code: 
    9783031013393 
    Verlag:  Springer 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 241 mm / B 160 mm / D 21 mm 
    Gewicht:  594 gr 
    Seiten:  284 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:

    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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