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

dc.contributor.authorKailong Liu
dc.contributor.authorYujie Wang
dc.contributor.authorXin Lai
dc.date.accessioned2026-04-30T21:25:16Z
dc.date.available2026-04-30T21:25:16Z
dc.date.issued2022
dc.descriptionLibro electrónico
dc.description.abstractThis 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.
dc.identifier.isbn978-3-319-69623-1157
dc.identifier.otherhttps://doi.org/10.1007/978-3-031-01340-9
dc.identifier.urihttps://link.springer.com/openurl?genre=book&isbn=978-3-031-01340-9
dc.identifier.urihttp://bibliovirtual.umar.mx:4000/handle/123456789/2465
dc.language.isoen_US
dc.publisherSpringer International Publishing
dc.titleData Science-Based Full-Lifespan Management of Lithium-Ion Battery
dc.typeBook
eperson.firstnamenombre
person.jobTitletrabajo

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