Real Time Determination of Rechargeable Batteries' Type and the State of Charge via Cascade Correlation Neural Network

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dc.authoridSOYLU, Emel/0000-0003-2774-9778
dc.contributor.authorBayir, Raif
dc.contributor.authorSoylu, Emel
dc.date.accessioned2024-09-29T16:09:57Z
dc.date.available2024-09-29T16:09:57Z
dc.date.issued2018
dc.departmentKarabük Üniversitesien_US
dc.description.abstractBatteries are used to store electrical energy as chemical energy. They have a wide using area from portable equipment to electric vehicles. It is important to know the state of charge of a battery to use it efficiently. In this study, a graphical user interface is developed using a visual programming language to monitor the electrical situations of batteries. Cascade neural network, which is one of the most chosen artificial neural networks, is used to determine the type and state of charge of batteries. The software is able to identify type and state of charge of batteries online. Lead acid, Lithium Ion, Lithium polymer, Nickel Cadmium, Nickel Metal Hydride rechargeable batteries are used in experiments. The experimental results indicate that accurate estimation results can be obtained by the proposed method.en_US
dc.identifier.doi10.5755/j01.eie.24.1.20150
dc.identifier.endpage30en_US
dc.identifier.issn1392-1215
dc.identifier.issue1en_US
dc.identifier.scopus2-s2.0-85042260116en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage25en_US
dc.identifier.urihttps://doi.org/10.5755/j01.eie.24.1.20150
dc.identifier.urihttps://hdl.handle.net/20.500.14619/7873
dc.identifier.volume24en_US
dc.identifier.wosWOS:000425817700004en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherKaunas Univ Technologyen_US
dc.relation.ispartofElektronika Ir Elektrotechnikaen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectArtificial neural networken_US
dc.subjectBattery monitoring softwareen_US
dc.subjectRechargeable batteriesen_US
dc.subjectState of charge determinationen_US
dc.titleReal Time Determination of Rechargeable Batteries' Type and the State of Charge via Cascade Correlation Neural Networken_US
dc.typeArticleen_US

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