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  • 1
    Online Resource
    Online Resource
    Data Science-Based Full-Lifespan Management of Lithium-Ion Battery : Manufacturing, Operation and Reutilization (2022)
    Cham :Springer International Publishing AG, | ©2022.
    Details
    UID:
    almahu_9949300186302882
    Format: 1 online resource (277 p.) : , illustrations (chiefly color).
    ISBN: 3-031-01340-9
    Series Statement: Green Energy and Technology.
    Content: 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.
    Note: Description based upon print version of record. , 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. , English
    Additional Edition: ISBN 3-031-01339-5
    Language: English
    Keywords: Electronic books. ; Electronic books. ; Electronic books ; Electronic books ; Electronic books.
    URL: Volltext  (kostenfrei)
    URL: Volltext  (kostenfrei)
    URL: kostenfrei
    URL: SpringerLink
    URL: Click here to view book
    URL: FULL  ((OIS Credentials Required))
    URL: FULL  ((OIS Credentials Required))
    URL: Click to View
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    Fulltext
    Fulltext
    Stabi Berlin
    HU Berlin
    Berlin International
    UB Potsdam
    EUV Frankfurt
    HTW Berlin
    FH Potsdam
    HPol Brandenburg
    BTU Cottbus
  • 2
    Online Resource
    Online Resource
    Data Science-Based Full-Lifespan Management of Lithium-Ion Battery : Manufacturing, Operation and Reutilization (2022)
    Cham : Springer International Publishing AG
    Details
    UID:
    gbv_1809172411
    Format: 1 online resource (277 pages)
    ISBN: 9783031013409
    Series Statement: Green Energy and Technology Ser.
    Content: Intro -- Foreword by Prof. Qing-Long Han -- Foreword by Prof. Jinyue Yan -- Preface -- Acknowledgments -- Contents -- About the Authors -- Abbreviations -- 1 Introduction to Battery Full-Lifespan Management -- 1.1 Background and Motivation -- 1.1.1 Energy Storage Market -- 1.1.2 Li-Ion Battery Role -- 1.2 Li-Ion Battery and Its Management -- 1.2.1 Li-Ion Battery -- 1.2.2 Demands for Battery Management -- 1.3 Data Science Technologies -- 1.3.1 What is Data Science -- 1.3.2 Type of Data Science Technologies -- 1.3.3 Performance Indicators -- 1.4 Summary -- References -- 2 Key Stages for Battery Full-Lifespan Management -- 2.1 Full-Lifespan of Li-Ion Battery -- 2.2 Li-Ion Battery Manufacturing -- 2.2.1 Battery Manufacturing Fundamental -- 2.2.2 Identifying Manufacturing Parameters and Variables -- 2.3 Li-Ion Battery Operation -- 2.3.1 Battery Operation Fundamental -- 2.3.2 Key Tasks of Battery Operation Management -- 2.4 Li-Ion Battery Reutilization -- 2.5 Summary -- References -- 3 Data Science-Based Battery Manufacturing Management -- 3.1 Overview of Battery Manufacturing -- 3.2 Data Science Application of Battery Manufacturing Management -- 3.2.1 Data Science Framework for Battery Manufacturing Management -- 3.2.2 Machine Learning Tool -- 3.3 Battery Electrode Manufacturing -- 3.3.1 Overview of Battery Electrode Manufacturing -- 3.3.2 Case 1: Battery Electrode Mass Loading Prediction with GPR -- 3.3.3 Case 2: Battery Electrode Property Classification with RF -- 3.4 Battery Cell Manufacturing -- 3.4.1 Overview of Battery Cell Manufacturing -- 3.4.2 Case 1: Battery Cell Capacities Prediction with SVR -- 3.4.3 Case 2: Battery Cell Capacity Classification with RUBoost -- 3.5 Summary -- References -- 4 Data Science-Based Battery Operation Management I -- 4.1 Battery Operation Modelling -- 4.1.1 Battery Electrical Model -- 4.1.2 Battery Thermal Model.
    Note: Description based on publisher supplied metadata and other sources
    Additional Edition: ISBN 9783031013393
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9783031013393
    Language: English
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    UB Potsdam
  • 3
    Online Resource
    Online Resource
    Data Science-Based Full-Lifespan Management of Lithium-Ion Battery : Manufacturing, Operation and Reutilization (2022)
    Cham :Springer International Publishing :
    Details
    UID:
    almahu_9949286421202882
    Format: XXIII, 258 p. 163 illus., 158 illus. in color. , online resource.
    Edition: 1st ed. 2022.
    ISBN: 9783031013409
    Series Statement: Green Energy and Technology,
    Content: 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.
    Note: 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.
    In: Springer Nature eBook
    Additional Edition: Printed edition: ISBN 9783031013393
    Additional Edition: Printed edition: ISBN 9783031013416
    Additional Edition: Printed edition: ISBN 9783031013423
    Language: English
    DOI: 10.1007/978-3-031-01340-9
    URL: https://doi.org/10.1007/978-3-031-01340-9
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Open Access Request
    HU Berlin
  • 4
    Online Resource
    Online Resource
    Data Science-Based Full-Lifespan Management of Lithium-Ion Battery : Manufacturing, Operation and Reutilization (2022)
    Cham :Springer International Publishing AG, | ©2022.
    Details
    UID:
    edocfu_9960678568702883
    Format: 1 online resource (277 p.) : , illustrations (chiefly color).
    ISBN: 3-031-01340-9
    Series Statement: Green Energy and Technology.
    Content: 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.
    Note: Description based upon print version of record. , 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. , English
    Additional Edition: ISBN 3-031-01339-5
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    FU Berlin
  • 5
    Online Resource
    Online Resource
    Data Science-Based Full-Lifespan Management of Lithium-Ion Battery : Manufacturing, Operation and Reutilization (2022)
    Cham :Springer International Publishing AG, | ©2022.
    Details
    UID:
    edoccha_9960678568702883
    Format: 1 online resource (277 p.) : , illustrations (chiefly color).
    ISBN: 3-031-01340-9
    Series Statement: Green Energy and Technology.
    Content: 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.
    Note: Description based upon print version of record. , 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. , English
    Additional Edition: ISBN 3-031-01339-5
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Charité
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