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Co-estimation of state of charge and capacity for battery packs in real electric vehicles with few representative cells and physics-informed machine learning

; ; ; ;

In
Energy : the international journal 306, Seiten/Artikel-Nr.:132520

ImpressumAmsterdam [u.a.] : Elsevier Science

Umfang[1]-13

ISSN0360-5442

Online
DOI: 10.1016/j.energy.2024.132520


Einrichtungen

  1. Lehrstuhl für Baustoffkunde (311110)
  2. Institut für Stromrichtertechnik und Elektrische Antriebe (614500)


Thematische Einordnung (Klassifikation)
DDC: 600


Dokumenttyp
Journal Article

Format
online, print

Sprache
English

Anmerkung
Peer reviewed article

Externe Identnummern
SCOPUS: SCOPUS:2-s2.0-85199264315
WOS Core Collection: WOS:001280210300001

Interne Identnummern
RWTH-2024-07578
Datensatz-ID: 990917

Beteiligte Länder
Germany, Peoples R China, Singapore

 GO

Medline ; Clarivate Analytics Master Journal List ; Current Contents - Engineering, Computing and Technology ; Ebsco Academic Search ; Essential Science Indicators ; IF >= 5 ; JCR ; NationallizenzNationallizenz ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection
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The record appears in these collections:
Document types > Articles > Journal Articles
Faculty of Electrical Engineering and Information Technology (Fac.6)
Faculty of Civil Engineering (Fac.3)
311110_20140620
Public records
Publications database
614500
 Record created 2024-08-13, last modified 2025-02-07
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