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

Berrueta, Javier; Berrueta Irigoyen, Alberto; Soto Cabria, Adrián; Sanchis Gúrpide, Pablo; Ursúa Rubio, Alfredo

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

dc.contributor.author	Berrueta, Javier
dc.contributor.author	Berrueta Irigoyen, Alberto
dc.contributor.author	Soto Cabria, Adrián
dc.contributor.author	Sanchis Gúrpide, Pablo
dc.contributor.author	Ursúa Rubio, Alfredo
dc.contributor.department	Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren	eu
dc.contributor.department	Institute of Smart Cities - ISC	en
dc.contributor.department	Ingeniería Eléctrica, Electrónica y de Comunicación	es_ES
dc.contributor.funder	Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa	es
dc.contributor.funder	Gobierno de Navarra / Nafarroako Gobernua	es
dc.date.accessioned	2022-09-19T10:13:23Z
dc.date.available	2022-11-03T00:00:15Z
dc.date.issued	2021
dc.date.updated	2022-09-19T08:42:12Z
dc.description.abstract	A 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.sponsorship	This 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.lift	2022-11-03
dc.embargo.terms	2022-11-03
dc.format.mimetype	application/pdf	en
dc.identifier.citation	Berrueta, 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.doi	10.1109/EEEIC/ICPSEurope51590.2021.9584520
dc.identifier.isbn	978-1-6654-3612-3
dc.identifier.uri	https://academica-e.unavarra.es/handle/2454/44069
dc.language.iso	eng	en
dc.publisher	IEEE	en
dc.relation.ispartof	Dicorato, M. (Ed.).: 2021 IEEE International Conference on Environment and Electrical Engineering and 2021 IEEE Industrial and Commercial Power Systems Europe. IEEE, 2021, 1 - 6, 978-1-6654-3612-0	en
dc.relation.projectID	info:eu-repo/grantAgreement/European Commission/Horizon 2020 Framework Programme/774094	en
dc.relation.projectID	info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-111262RB-I00/ES/	en
dc.relation.publisherversion	https://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.accessRights	Acceso abierto / Sarbide irekia	es
dc.rights.accessRights	info:eu-repo/semantics/openAccess	en
dc.subject	Lithium-ion battery	en
dc.subject	State of charge	en
dc.subject	Kalman Filter	en
dc.subject	Estimation algorithm	en
dc.title	Particularised Kalman filter for the state-of-charge estimation of second-life lithium-ion batteries and experimental validation	en
dc.type	Contribución a congreso / Biltzarrerako ekarpena	es
dc.type	info:eu-repo/semantics/conferenceObject	en
dc.type.version	Versión aceptada / Onetsi den bertsioa	es
dc.type.version	info:eu-repo/semantics/acceptedVersion	en
dspace.entity.type	Publication
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