Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/107854
DC FieldValueLanguage
dc.contributorDepartment of Electrical and Electronic Engineering-
dc.creatorLiu, W-
dc.creatorChau, KT-
dc.date.accessioned2024-07-15T07:54:51Z-
dc.date.available2024-07-15T07:54:51Z-
dc.identifier.isbn978-981-99-3059-3 (Hardcover)-
dc.identifier.isbn978-981-99-3062-3 (Softcover)-
dc.identifier.isbn978-981-99-3060-9 (eBook)-
dc.identifier.urihttp://hdl.handle.net/10397/107854-
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.titleBattery management technologies in hybrid and electric vehiclesen_US
dc.typeBook Chapteren_US
dc.identifier.spage219-
dc.identifier.epage248-
dc.identifier.doi10.1007/978-981-99-3060-9_8-
dcterms.abstractHybrid electric vehicles (HEVs) and electric vehicles (EVs) have been advocated by global governments’ policies in recent decades. Besides combating the climate crisis and urban air pollution, great contributions of developing the HEVs and EVs have been identified to accelerate the process of green transportation and smart city. Battery management is one of the most crucial functions for HEVs and EVs. It can ensure safe operation and optimize the performance of EV batteries. This chapter discusses the mainstream technologies of battery management in HEVs and EVs. Wherein, battery management technologies, including battery modeling, battery state estimation, safety prognostic (such as thermal management), and fault diagnosis, are elaborated in detail. Among them, the data-driven method is most effective and promising for battery state estimation (such as for state of charge and state of temperature) and health diagnosis or prognostics with impressive accuracy. Besides, some emerging management technologies, including multi-model co-estimation, artificial intelligence, cloud computing technology, and blockchain technology, are briefed, which can play a significant role in coordinating the information and energy flows in a vehicular information and energy internet.-
dcterms.accessRightsembargoed accessen_US
dcterms.bibliographicCitationIn CHT Lee (Eds.). Emerging Technologies for Electric and Hybrid Vehicles, p. 219-248. Singapore: Springer Nature, 2024-
dcterms.issued2024-
dc.identifier.scopus2-s2.0-85183583773-
dc.description.validate202407 bcch-
dc.identifier.FolderNumbera3010ben_US
dc.identifier.SubFormID49171en_US
dc.description.fundingSourceRGCen_US
dc.description.pubStatusPublisheden_US
dc.date.embargo2025-01-28en_US
dc.description.oaCategoryGreen (AAM)en_US
Appears in Collections:Book Chapter
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Embargo End Date 2025-01-28
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