Data Science-Based Full-Lifespan Management of Lithium-Ion Battery

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) batter...

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Main Authors: Liu, Kailong, Wang, Yujie, Lai, Xin
格式: Online
語言:英语
出版: Springer Nature 2022
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在線閱讀:ONIX_20220413_9783031013409_27
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author Liu, Kailong
Wang, Yujie
Lai, Xin
author_browse Lai, Xin
Liu, Kailong
Wang, Yujie
author_facet Liu, Kailong
Wang, Yujie
Lai, Xin
author_sort Liu, Kailong
collection Directory of Open Access Books
description 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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spelling doab-20.500.12854ir-815202025-07-30T11:55:39Z Data Science-Based Full-Lifespan Management of Lithium-Ion Battery Liu, Kailong Wang, Yujie Lai, Xin Lithium-ion Battery Battery Manufacturing Management Battery Operation Management Battery Recycling Management Data Science Artificial Intelligence Open Access thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials::TGM Materials science thema EDItEUR::U Computing and Information Technology::UN Databases thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials::TGM Materials science thema EDItEUR::U Computing and Information Technology::UN Databases thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering 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. 2022-05-13T00:42:18Z 2022-05-13T00:42:18Z 2022-04-13T15:09:10Z 2022 book ONIX_20220413_9783031013409_27 OCN: 1310785741 https://library.oapen.org/handle/20.500.12657/54032 9783031013409 https://directory.doabooks.org/handle/20.500.12854/81520 eng Green Energy and Technology open access image/jpeg image/jpeg image/jpeg n/a n/a n/a https://library.oapen.org/bitstream/20.500.12657/54032/1/978-3-031-01340-9.pdf https://library.oapen.org/bitstream/20.500.12657/54032/1/978-3-031-01340-9.pdf https://library.oapen.org/bitstream/20.500.12657/54032/1/978-3-031-01340-9.pdf Springer Nature Springer International Publishing 10.1007/978-3-031-01340-9 10.1007/978-3-031-01340-9 9fa3421d-f917-4153-b9ab-fc337c396b5a 9783031013409 Springer International Publishing 258 Cham open access
spellingShingle Lithium-ion Battery
Battery Manufacturing Management
Battery Operation Management
Battery Recycling Management
Data Science
Artificial Intelligence
Open Access
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials::TGM Materials science
thema EDItEUR::U Computing and Information Technology::UN Databases
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials::TGM Materials science
thema EDItEUR::U Computing and Information Technology::UN Databases
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering
Liu, Kailong
Wang, Yujie
Lai, Xin
Data Science-Based Full-Lifespan Management of Lithium-Ion Battery
title Data Science-Based Full-Lifespan Management of Lithium-Ion Battery
title_full Data Science-Based Full-Lifespan Management of Lithium-Ion Battery
title_fullStr Data Science-Based Full-Lifespan Management of Lithium-Ion Battery
title_full_unstemmed Data Science-Based Full-Lifespan Management of Lithium-Ion Battery
title_short Data Science-Based Full-Lifespan Management of Lithium-Ion Battery
title_sort data science based full lifespan management of lithium ion battery
topic Lithium-ion Battery
Battery Manufacturing Management
Battery Operation Management
Battery Recycling Management
Data Science
Artificial Intelligence
Open Access
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials::TGM Materials science
thema EDItEUR::U Computing and Information Technology::UN Databases
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials::TGM Materials science
thema EDItEUR::U Computing and Information Technology::UN Databases
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering
topic_facet Lithium-ion Battery
Battery Manufacturing Management
Battery Operation Management
Battery Recycling Management
Data Science
Artificial Intelligence
Open Access
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials::TGM Materials science
thema EDItEUR::U Computing and Information Technology::UN Databases
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials::TGM Materials science
thema EDItEUR::U Computing and Information Technology::UN Databases
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering
url ONIX_20220413_9783031013409_27
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