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dc.contributor.authorVenegas, Pablo
dc.contributor.authorGómez Pedreira, Dolores
dc.contributor.authorArrinda, Mikel
dc.contributor.authorOyarbide, Mikel
dc.contributor.authorMacicior, Haritz
dc.contributor.authorBermúdez de Castro López-Varela, Alfredo
dc.date.accessioned2022-06-02T06:52:27Z
dc.date.available2022-06-02T06:52:27Z
dc.date.issued2022
dc.identifier.citationVenegas, P., Gómez, D., Arrinda, M., Oyarbide, M., Macicior, H., Bermúdez, A. Kalman filter and classical Preisach hysteresis model applied to the state of charge battery estimation. Comput. Math. Appl. 118 (2022), 74-84.
dc.identifier.issn0898-1221
dc.identifier.urihttp://hdl.handle.net/10347/28777
dc.description.abstractThe goal of this work is first to include a hysteresis model in the classical equivalent circuit model (ECM) for a battery system and then to improve the estimation of the state of charge (SoC) by applying the Extended Kalman Filter (EKF). The hysteretic behavior of the open circuit voltage (OCV) is modelled with the classical Preisach model used for magnetic materials. The construction of the Preisach operator is made by means of the Everett function identified from experimental data which only involve the charging curves of the battery. Thus, a significant reduction in the time necessary to obtain the measurements is achieved. The model is assessed with some laboratory experiments performed on a lithium-ion battery and the results show that with this procedure hysteresis is very well reproduced, even when interior loops are present. In addition, the use of the EKF allows us to eliminate the measurements noise and ensure the accuracy of SoC estimation. The high computational efficiency and precision of the method, joined to the limited computational resources needed for the numerical implementation, make it particularly suitable for real-time embedded battery management system (BMS) applications. In addition, the proposed methodology is well-adapted to any battery type, independently of the SoC-OCV profile of the hysteresis cycle
dc.description.sponsorshipThis work has been partially supported by FEDER, Ministerio de Economía, Industria y Competitividad-AEI research project MTM2017-86459-R, by Xunta de Galicia (Spain) research project GI-1563 ED431C 2021/15, by DIUBB through project 2120173 GI/C and by ANID-Chile through FONDECYT grant 1211030 and Centro de Modelamiento Matemático (CMM), ACE210010 and FB210005, BASAL funds for centers of excellence from ANID-Chile.
dc.language.isoeng
dc.publisherElsevier
dc.relationinfo:eu-repo/grantAgreement/MTM2017-86459-R/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/ES/APLICACIONES DE LA MODELIZACION, LA SIMULACION NUMERICA, LA OPTIMIZACION Y EL CONTROL OPTIMO AL DISEÑO DE DISPOSITIVOS Y PROCESOS INDUSTRIALES
dc.rights© 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/li- censes/by-nc-nd/4.0/)
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectHysteresis modelling
dc.subjectPreisach model
dc.subjectExtended Kalman filter
dc.subjectState of charge estimation
dc.subjectLithium-ion battery
dc.titleKalman filter and classical Preisach hysteresis model applied to the state of charge battery estimation
dc.typeinfo:eu-repo/semantics/article
dc.identifier.DOI10.1016/j.camwa.2022.05.009
dc.relation.publisherversionhttps://doi.org/10.1016/j.camwa.2022.05.009
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.contributor.affiliationUniversidade de Santiago de Compostela. Departamento de Matemática Aplicada
dc.description.peerreviewedSI


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© 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/li- censes/by-nc-nd/4.0/)
Except where otherwise noted, this item's license is described as  © 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/li- censes/by-nc-nd/4.0/)





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