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Transforming 3D multi-physics simulations into real-time onboard intelligence for energy storage systems thermal management with physics-informed neural networks

; ; ; ; ; ;

In
Applied energy 418, Seiten/Artikel-Nr.:128057

ImpressumAmsterdam [u.a.] : Elsevier Science

Umfang[1]-22

ISSN1872-9118

Online
DOI: 10.1016/j.apenergy.2026.128057


Einrichtungen

  1. Institut für Stromrichtertechnik und Elektrische Antriebe (614500)
  2. Juniorprofessur für Artificial Intelligence and Digitalization for Batteries (619830)
  3. Center for Ageing, Reliability and Lifetime Prediction of Electrochemical and Power Electronic Systems (080070)


Thematische Einordnung (Klassifikation)
DDC: 620


Dokumenttyp
Journal Article

Format
online, print

Sprache
English

Anmerkung
Peer reviewed article

Externe Identnummern
SCOPUS: SCOPUS:2-s2.0-105039026317
WOS Core Collection: WOS:001780417200001

Interne Identnummern
RWTH-2026-06106
Datensatz-ID: 1037587

Beteiligte Länder
Germany, Peoples R China

Lizenzstatus der Zeitschrift

 GO

Medline ; Clarivate Analytics Master Journal List ; Current Contents - Engineering, Computing and Technology ; Ebsco Academic Search ; Essential Science Indicators ; IF >= 10 ; JCR ; 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)
Central and Other Institutions
Public records
Publications database
614500
080070
 Record created 2026-06-19, last modified 2026-07-23
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