Particularised Kalman filter for the state-of-charge estimation of second-life lithium-ion batteries and experimental validation

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dc.contributor.authorBerrueta, Javier
dc.contributor.authorBerrueta Irigoyen, Alberto
dc.contributor.authorSoto Cabria, Adrián
dc.contributor.authorSanchis Gúrpide, Pablo
dc.contributor.authorUrsúa Rubio, Alfredo
dc.contributor.departmentIngeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzareneu
dc.contributor.departmentInstitute of Smart Cities - ISCen
dc.contributor.departmentIngeniería Eléctrica, Electrónica y de Comunicaciónes_ES
dc.contributor.funderUniversidad Pública de Navarra / Nafarroako Unibertsitate Publikoaes
dc.contributor.funderGobierno de Navarra / Nafarroako Gobernuaes
dc.date.accessioned2022-09-19T10:13:23Z
dc.date.available2022-11-03T00:00:15Z
dc.date.issued2021
dc.date.updated2022-09-19T08:42:12Z
dc.description.abstractA critical issue for a proper energy management of a lithium-ion (Li-ion) battery is the estimation of its state-of-charge (SOC). There are various methods available for the SOC estimation, being some of them robust and accurate, but requiring high computational power for its applicability, which is inconvenient for their use with the usual low-cost microcontrollers that build a typical BMS. This contribution proposes an SOC estimation algorithm based on a simplified Kalman Filter, that combines a high accuracy with reduced computational requirements. The proposed simplifications result from a careful analysis of the Li-ion battery performance and linearization of processes that entail negligible loss of accuracy. The proposed algorithm is used to estimate the SOC of a second-life Li-ion battery operating in an experimental PV self-consumption facility. Its performance, in terms of accuracy, robustness and computational requirement, is compared with an Extended Kalman Filter (EKF), a Particle Filter (PF) and other low-performance estimation algorithms, proving its tradeoff between accuracy and computational cost.en
dc.description.sponsorshipThis work has been supported by the Spanish State Research Agency (AEI) under grant PID2019-111262RB-I00 /AEI/ 10.13039/501100011033, the European Union under the H2020 project STARDUST (774094), the Government of Navarra through research project 0011–1411–2018–000029 GERA and the Public University of Navarra under project ReBMS PJUPNA1904.en
dc.embargo.lift2022-11-03
dc.embargo.terms2022-11-03
dc.format.mimetypeapplication/pdfen
dc.identifier.citationBerrueta, J.; Berrueta, A.; Soto, A.; Sanchis, P.; Ursúa, A.. (2021). Particularised Kalman Filter for the state-of-charge estimation of second-life lithium-ion batteries and experimental validation. 1 IEEE; (p. 1-6).en
dc.identifier.doi10.1109/EEEIC/ICPSEurope51590.2021.9584520
dc.identifier.isbn978-1-6654-3612-3
dc.identifier.urihttps://academica-e.unavarra.es/handle/2454/44069
dc.language.isoengen
dc.publisherIEEEen
dc.relation.ispartofDicorato, M. (Ed.).: 2021 IEEE International Conference on Environment and Electrical Engineering and 2021 IEEE Industrial and Commercial Power Systems Europe. IEEE, 2021, 1 - 6, 978-1-6654-3612-0en
dc.relation.projectIDinfo:eu-repo/grantAgreement/European Commission/Horizon 2020 Framework Programme/774094/
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-111262RB-I00/ES/
dc.relation.publisherversionhttps://doi.org/10.1109/EEEIC/ICPSEurope51590.2021.9584520
dc.rights© 2021 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 work.en
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.subjectLithium-ion batteryen
dc.subjectState of chargeen
dc.subjectKalman Filteren
dc.subjectEstimation algorithmen
dc.titleParticularised Kalman filter for the state-of-charge estimation of second-life lithium-ion batteries and experimental validationen
dc.typeinfo:eu-repo/semantics/conferenceObject
dc.type.versioninfo:eu-repo/semantics/acceptedVersion
dspace.entity.typePublication
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relation.isAuthorOfPublication.latestForDiscoverye2fc78a7-4a1b-45eb-86f4-fe9ad125c1a9

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