Prediction of charge-discharge behavior and state of charge estimation for tri-electrode rechargeable zinc-air flow batteries

dc.contributor.authorLao-atiman W.
dc.contributor.authorBumroongsri P.
dc.contributor.authorArpornwichanop A.
dc.contributor.authorOlaru S.
dc.contributor.authorKheawhom S.
dc.contributor.otherMahidol University
dc.date.accessioned2023-06-18T17:08:58Z
dc.date.available2023-06-18T17:08:58Z
dc.date.issued2022-11-30
dc.description.abstractAn effective state of charge (SOC) estimation is essential for the development of a battery management system. At present, the provision of a SOC estimation for zinc-air flow batteries (ZAFBs) is still at its early stage of development. This work sets out to develop the SOC estimator for ZAFBs. The estimator is based-on a linear parameter varying (LPV) model integrated with an extended Kalman filter (EKF). The LPV model is constructed from multiple linear time-invariant (LTI) models with battery current and SOC as scheduling parameters. It is observed that the response data for ZAFBs have an exceptionally flat profile related to SOC change; dynamic differentiation only occurs when SOC is almost depleted. For this reason, the estimation of SOC converges to the true value when SOC is near depletion. In this work, it is shown that by appropriate tuning, the SOC estimation performance of the LPV model combined with EKF performs well as the absolute errors of soc. estimation lie under 2 % after true SOC convergence. The LPV model with the EKF algorithm is also compared with the Luenberger observer (LO). The proposed estimator can surpass the LO estimator. Overall, this SOC estimator provides a systematic way to fulfill the requirements of a battery management system.
dc.identifier.citationJournal of Energy Storage Vol.55 (2022)
dc.identifier.doi10.1016/j.est.2022.105786
dc.identifier.eissn2352152X
dc.identifier.scopus2-s2.0-85139344482
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/123456789/84543
dc.rights.holderSCOPUS
dc.subjectEnergy
dc.titlePrediction of charge-discharge behavior and state of charge estimation for tri-electrode rechargeable zinc-air flow batteries
dc.typeArticle
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85139344482&origin=inward
oaire.citation.titleJournal of Energy Storage
oaire.citation.volume55
oairecerif.author.affiliationChulalongkorn University
oairecerif.author.affiliationMahidol University
oairecerif.author.affiliationLaboratoire des Signaux et Systèmes

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