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Titlebook: Data Science-Based Full-Lifespan Management of Lithium-Ion Battery; Manufacturing, Opera Kailong Liu,Yujie Wang,Xin Lai Book‘‘‘‘‘‘‘‘ 2022 T

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发表于 2025-3-21 19:06:03 | 显示全部楼层 |阅读模式
书目名称Data Science-Based Full-Lifespan Management of Lithium-Ion Battery
副标题Manufacturing, Opera
编辑Kailong Liu,Yujie Wang,Xin Lai
视频video
概述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
丛书名称Green Energy and Technology
图书封面Titlebook: Data Science-Based Full-Lifespan Management of Lithium-Ion Battery; Manufacturing, Opera Kailong Liu,Yujie Wang,Xin Lai Book‘‘‘‘‘‘‘‘ 2022 T
描述.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 introdu
出版日期Book‘‘‘‘‘‘‘‘ 2022
关键词Lithium-ion Battery; Battery Manufacturing Management; Battery Operation Management; Battery Recycling
版次1
doihttps://doi.org/10.1007/978-3-031-01340-9
isbn_softcover978-3-031-01342-3
isbn_ebook978-3-031-01340-9Series ISSN 1865-3529 Series E-ISSN 1865-3537
issn_series 1865-3529
copyrightThe Editor(s) (if applicable) and The Author(s) 2022
The information of publication is updating

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Martin Hohenadler,Thomas C. Langfinal battery performance is crucial but still remains a difficult challenge. Recent advancements in data-driven analytic and related machine learning strategies raised interest in data science methods to perform effective and reasonable management of battery manufacturing.
发表于 2025-3-22 15:37:35 | 显示全部楼层
Introduction to Battery Full-Lifespan Management,apter first introduces the background and motivation of Li-ion battery, followed by the description of Li-ion battery fundamentals and the demands of battery management. After that, the basic information and benefits of using data science technologies to achieve effective battery full-lifespan management are presented.
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发表于 2025-3-23 00:29:25 | 显示全部楼层
1865-3529 t and real case studies.Consolidates studies in the rapidly .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 batterie
发表于 2025-3-23 05:21:07 | 显示全部楼层
Introduction to Molecular Dynamicsfirst offer the concept and give a systematic framework for the full-lifespan of Li-ion battery, which can be mainly divided into three stages including the battery manufacturing, battery operation, and battery reutilization. Then key management tasks of each stage would be introduced in detail.
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