Implementation of hardware-in-the-loop based platform for real-time battery state of charge estimation on li-ion batteries of electric vehicles using multilayer perceptron

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dc.contributor.authorÇeven, S.
dc.contributor.authorBayir, R.
dc.date.accessioned2024-09-29T16:16:27Z
dc.date.available2024-09-29T16:16:27Z
dc.date.issued2020
dc.departmentKarabük Üniversitesien_US
dc.description.abstractIn this study, hardware-in-the-loop based real-time state of charge estimation was performed in Li-Ion batteries, which are widely used in hybrid and battery electric vehicles. The state of charge is estimated on the Li-Ion battery cell that forms the electric vehicle battery system. Multi-layer perceptron approach has been preferred as a method for estimating the battery state of charge. Discharge experiments based on different electrical loads were applied to the Li-Ion battery cell to be used in multilayer perceptron learning processes. An experimental setup has been prepared to perform the discharge process under different electrical loads. In each discharge experiment, battery open circuit voltage, battery discharge current and battery cell temperature parameters were measured and were recorded. By using the data obtained from the experiments on the battery cell, a multilayer perceptron model was created in MATLAB environment. After creating the multilayer perceptron model, the real-time battery state of charge the was estimated at different discharge currents in the experimental setup and the results obtained were evaluated. © 2020, Ismail Saritas. All rights reserved.en_US
dc.identifier.doi10.18201/ijisae.2020466313
dc.identifier.endpage205en_US
dc.identifier.issn2147-6799
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-85100221415en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage195en_US
dc.identifier.urihttps://doi.org/10.18201/ijisae.2020466313
dc.identifier.urihttps://hdl.handle.net/20.500.14619/9103
dc.identifier.volume8en_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIsmail Saritasen_US
dc.relation.ispartofInternational Journal of Intelligent Systems and Applications in Engineeringen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectArtificial neural networksen_US
dc.subjectElectric vehiclesen_US
dc.subjectHardware-in-the-loopen_US
dc.subjectLi-Ion batteriesen_US
dc.subjectMultilayer perceptronen_US
dc.subjectState of charge estimationen_US
dc.titleImplementation of hardware-in-the-loop based platform for real-time battery state of charge estimation on li-ion batteries of electric vehicles using multilayer perceptronen_US
dc.typeArticleen_US

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