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Data Science-Based Full-Lifespan Management of Lithium-Ion Battery - Manufacturing, Operation and Reutilization (Hardcover, 1st ed. 2022) Loot Price: R1,702
Discovery Miles 17 020
Data Science-Based Full-Lifespan Management of Lithium-Ion Battery - Manufacturing, Operation and Reutilization (Hardcover, 1st...

Data Science-Based Full-Lifespan Management of Lithium-Ion Battery - Manufacturing, Operation and Reutilization (Hardcover, 1st ed. 2022)

Kailong Liu, Yujie Wang, Xin Lai

Series: Green Energy and Technology

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Loot Price R1,702 Discovery Miles 17 020 | Repayment Terms: R160 pm x 12*

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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.

General

Imprint: Springer International Publishing AG
Country of origin: Switzerland
Series: Green Energy and Technology
Release date: April 2022
First published: 2022
Authors: Kailong Liu • Yujie Wang • Xin Lai
Dimensions: 235 x 155mm (L x W)
Format: Hardcover
Pages: 258
Edition: 1st ed. 2022
ISBN-13: 978-3-03-101339-3
Categories: Books > Professional & Technical > Energy technology & engineering > General
Books > Professional & Technical > Mechanical engineering & materials > Materials science > General
Books > Computing & IT > Applications of computing > Databases > General
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LSN: 3-03-101339-5
Barcode: 9783031013393

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