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dc.creatorBraco Sola, Elisaes_ES
dc.creatorSan Martín Biurrun, Idoiaes_ES
dc.creatorSanchis Gúrpide, Pabloes_ES
dc.creatorUrsúa Rubio, Alfredoes_ES
dc.date.accessioned2023-03-30T17:44:15Z
dc.date.available2023-03-30T17:44:15Z
dc.date.issued2023
dc.identifier.citationBraco, E., San Martín, I., Sanchis, P., & Ursúa, A. (2023). Fast capacity and internal resistance estimation method for second-life batteries from electric vehicles. Applied Energy, 329, 120235. https://doi.org/10.1016/j.apenergy.2022.120235en
dc.identifier.issn0306-2619
dc.identifier.urihttps://hdl.handle.net/2454/44994
dc.description.abstractThe success of second-life (SL) Li-ion batteries from electric vehicles is still conditioned by their technical and economic viability. The knowledge of the internal parameters of retired batteries at the repurposing stage is key to ensure their adequate operation and to enlarge SL lifetime. However, traditional characterization methods require long testing times and specific equipment, which result in high costs that may jeopardize the economic viability of SL. In the seek of optimizing the repurposing stage, this contribution proposes a novel fast characterization method that allows to estimate capacity and internal resistance at various state of charge for reused cells, modules and battery packs. Three estimation models are proposed. The first of them is based on measurements of AC resistance, the second on DC resistance and the third combines both resistance types. These models are validated in 506 cells, 203 modules and 3 battery packs from different Nissan Leaf vehicles. The results achieved are satisfactory, with mean absolute percentage errors (MAPE) below 2.5% at cell and module level in capacity prediction and lower than 2.4% in resistance estimation. Considering battery pack level, MAPE is below 4.2% and 1.8% in capacity and resistance estimation respectively. With the proposed method, testing times are reduced from more than one day to 2 min per cell, while energy consumption is lowered from 1.4 kWh to 1 Wh. In short, this study contributes to the reduction of repurposing procedures and costs, and ultimately to the success of SL batteries business model.en
dc.description.sponsorshipThis work is part of the projects PID2019-111262RB-I00, funded by MCIN/AEI, Spain/10.13039/501100011033/, STARDUST (774094), funded by European Union’s Horizon 2020 research and innovation programme, HYBPLANT, Spain (0011-1411-2022-000039), funded by Government of Navarre, Spain, and a Ph.D. scholarship, also funded by Government of Navarre, Spain . Open access funding provided by Universidad Pública de Navarra, Spain .en
dc.format.mimetypeapplication/pdfen
dc.language.isoengen
dc.publisherElsevieren
dc.relation.ispartofApplied Energy 329 (2023) 120235en
dc.rights© 2022 The Author(s). This is an open access article under the CC BY license.en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectCharacterizationen
dc.subjectElectric vehicleen
dc.subjectEnergy storageen
dc.subjectLithium-ion batteryen
dc.subjectSecond-life batteryen
dc.titleFast capacity and internal resistance estimation method for second-life batteries from electric vehiclesen
dc.typeArtículo / Artikuluaes
dc.typeinfo:eu-repo/semantics/articleen
dc.date.updated2023-03-30T17:23:52Z
dc.contributor.departmentIngeniería Eléctrica, Electrónica y de Comunicaciónes_ES
dc.contributor.departmentIngeniaritza Elektrikoa, Elektronikoa eta Telekomunikazio Ingeniaritzaeu
dc.contributor.departmentInstitute of Smart Cities - ISCen
dc.rights.accessRightsAcceso abierto / Sarbide irekiaes
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen
dc.identifier.doi10.1016/j.apenergy.2022.120235
dc.relation.projectIDinfo:eu-repo/grantAgreement/European Commission/Horizon 2020 Framework Programme/774094en
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-111262RB-I00/ES/en
dc.relation.projectIDinfo:eu-repo/grantAgreement/Gobierno de Navarra/0011-1411-2022-000039en
dc.relation.publisherversionhttps://doi.org/10.1016/j.apenergy.2022.120235
dc.type.versionVersión publicada / Argitaratu den bertsioaes
dc.type.versioninfo:eu-repo/semantics/publishedVersionen
dc.contributor.funderUniversidad Pública de Navarra / Nafarroako Unibertsitate Publikoaes


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© 2022 The Author(s). This is an open access article under the CC BY license.
Except where otherwise noted, this item's license is described as © 2022 The Author(s). This is an open access article under the CC BY license.

El Repositorio ha recibido la ayuda de la Fundación Española para la Ciencia y la Tecnología para la realización de actividades en el ámbito del fomento de la investigación científica de excelencia, en la Línea 2. Repositorios institucionales (convocatoria 2020-2021).
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