國立高雄大學圖資館 |

Language: English

Back

Data science-based full-lifespan management of lithium-ion batterymanufacturing, operation and reutilization /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Data science-based full-lifespan management of lithium-ion batteryby Kailong Liu, Yujie Wang, Xin Lai.
Reminder of title:	manufacturing, operation and reutilization /
Author:	Liu, Kailong.
other author:	Wang, Yujie.
Published:	Cham :Springer International Publishing :2022.
Description:	xxiii, 258 p. :ill. (chiefly col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Lithium ion batteries.
Online resource:	https://doi.org/10.1007/978-3-031-01340-9
ISBN:	9783031013409$q(electronic bk.)

Data science-based full-lifespan management of lithium-ion batterymanufacturing, operation and reutilization /
Liu, Kailong.

Data science-based full-lifespan management of lithium-ion batterymanufacturing, operation and reutilization /[electronic resource] :by Kailong Liu, Yujie Wang, Xin Lai. - Cham :Springer International Publishing :2022. - xxiii, 258 p. :ill. (chiefly col.), digital ;24 cm. - Green energy and technology,1865-3537. - Green energy and technology..

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.

Open access.

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.

ISBN: 9783031013409$q(electronic bk.)

Standard No.: 10.1007/978-3-031-01340-9doiSubjects--Topical Terms:

549762
Lithium ion batteries.

LC Class. No.: TK2945.L58 / L58 2022

Dewey Class. No.: 621.312424

Data science-based full-lifespan management of lithium-ion batterymanufacturing, operation and reutilization /
LDR:02953nmm a2200373 a 4500 001 621007
003 DE-He213
005 20220408222535.0
006 m d
007 cr nn 008maaau
008 221121s2022 sz s 0 eng d
020 $a 9783031013409$q(electronic bk.)
020 $a 9783031013393$q(paper)
024 7 $a 10.1007/978-3-031-01340-9 $2 doi
035 $a 978-3-031-01340-9
040 $a GP $c GP
041 0 $a eng
050 4 $a TK2945.L58 $b L58 2022
072 7 $a TGM $2 bicssc
072 7 $a PNRH $2 bicssc
072 7 $a TEC021000 $2 bisacsh
072 7 $a TGMM $2 thema
072 7 $a PNRH $2 thema
082 0 4 $a 621.312424 $2 23
090 $a TK2945.L58 $b L783 2022
100 1 $a Liu, Kailong. $3 922005
245 1 0 $a Data science-based full-lifespan management of lithium-ion battery $h [electronic resource] : $b manufacturing, operation and reutilization / $c by Kailong Liu, Yujie Wang, Xin Lai.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2022.
300 $a xxiii, 258 p. : $b ill. (chiefly col.), digital ; $c 24 cm.
490 1 $a Green energy and technology, $x 1865-3537
505 0 $a 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.
506 $a Open access.
520 $a 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.
650 0 $a Lithium ion batteries. $3 549762
650 0 $a Battery management systems. $3 866110
650 1 4 $a Batteries. $3 918987
650 2 4 $a Materials for Energy and Catalysis. $3 918934
650 2 4 $a Data Engineering. $3 839346
650 2 4 $a Electrical Power Engineering. $3 919410
700 1 $a Wang, Yujie. $3 922006
700 1 $a Lai, Xin. $3 922007
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a Green energy and technology. $3 558129
856 4 0 $u https://doi.org/10.1007/978-3-031-01340-9
950 $a Engineering (SpringerNature-11647)