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Module-Level Modelling Approach for a Cloudbased Digital Twin Platform for Li-Ion Batteries.pdf (504.1Kb)
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Title
Module-Level Modelling Approach for a Cloudbased Digital Twin Platform for Li-Ion Batteries
Author
Miguel, Eduardo
IRAOLA, UNAI
Author (from another institution)
Lizaso-Eguileta, Olatz
Martínez Laserna, Egoitz
Rivas, Mikel
Cantero, Igor
Research Group
Almacenamiento de energía
Other institutions
Ikerlan
Cegasa Energia S.L.U.
Version
Postprint
Rights
© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Access
Open access
URI
https://hdl.handle.net/20.500.11984/5605
Publisher’s version
https://doi.org/10.1109/VPPC53923.2021.9699271
Published at
2021 IEEE Vehicle Power and Propulsion Conference (VPPC) 
Publisher
IEEE
Keywords
digital twin
Cloud computing
Battery models
State of Charge
Abstract
The pursue of the new increasingly intelligent, and heavier state estimation algorithms requires a significant amount of data and computing power, which may challenge their deployment in current BMS s ... [+]
The pursue of the new increasingly intelligent, and heavier state estimation algorithms requires a significant amount of data and computing power, which may challenge their deployment in current BMS solutions. To address that issue, this paper proposes a cloud-based Digital Twin Platform to extend computing power and data storage capacity. This tool aims to contain the integration of models to analyse thermoelectricand ageing aspects of a LIB, based on experimental operation data by comparative analysis. Based on well-known cell-level modelling techniques, a module-level modelling approach is proposed and an experimental validation platform is suggested. [-]
xmlui.dri2xhtml.METS-1.0.item-sponsorship
Gobierno Vasco
xmlui.dri2xhtml.METS-1.0.item-projectID
info:eu-repo/grantAgreement/GV/Programa Bikaintek 2019/20-AF-W2-2019-00005/CAPV//
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