Using artificial neural networks to improve the efficiency of transformers used in wireless power transmission systems for different coil positions

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dc.authorid0000-0001-8461-8702en_US
dc.authorid0000-0002-0181-3658en_US
dc.contributor.authorÖzüpak, Yıldırım
dc.contributor.authorAslan, Emrah
dc.date.accessioned2024-08-16T12:13:53Z
dc.date.available2024-08-16T12:13:53Z
dc.date.issued2024en_US
dc.departmentDicle Üniversitesi, Silvan Meslek Yüksek Okulu, Elektrik ve Enerji Bölümüen_US
dc.description.abstractThis study uses magnetic resonance-based coupling theory to study the various placements of transmitter and receiver coils in wireless power transfer (WPT) systems. Various coil placements are examined to show where high efficiency can be achieved within the air gap. Basic characteristics such as self-inductance, mutual inductance, and coupling coefficient were calculated. Artificial neural networks (ANNs) in WPT are a powerful technique for predicting performance characteristics. Using ANNs provides an excellent method for streamlining the design process and reducing time-consuming calculations. To quickly determine and optimize coil design, this study compares recent research on ANN applications in WPT and the performance of different types of ANNs in WPT systems. An artificial neural network (ANN) was trained to predict the magnetic properties of a wireless power transfer (WPT) device. Appropriate cost functions have been implemented to train the ANN properly. It was shown that the trained ANN can effectively reproduce the data obtained by the finite element method (FEM). The results show an effective power transmission at different coil placements, with decreased efficiency observed after a certain distance. These data will help determine the proposed WPT system's air gap and angular limits.en_US
dc.identifier.citationÖzüpak, Y. ve Aslan, E. (2024). Using artificial neural networks to improve the efficiency of transformers used in wireless power transmission systems for different coil positions. Revue Roumaine des Sciences Techniques Serie Electrotechnique et Energetique, 69(2), 195-200.en_US
dc.identifier.endpage200en_US
dc.identifier.issn0035-4066
dc.identifier.issue2en_US
dc.identifier.scopus2-s2.0-85199289242
dc.identifier.scopusqualityQ3
dc.identifier.startpage195en_US
dc.identifier.urihttps://journal.iem.pub.ro/rrst-ee/article/view/611
dc.identifier.urihttps://hdl.handle.net/11468/28754
dc.identifier.volume69en_US
dc.identifier.wosWOS:001265977200013
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorÖzüpak, Yıldırım
dc.institutionauthorAslan, Emrah
dc.language.isoenen_US
dc.publisherPublishing House of the Romanian Academyen_US
dc.relation.ispartofRevue Roumaine des Sciences Techniques Serie Electrotechnique et Energetique
dc.relation.isversionof10.59277/RRST-EE.2024.2.13en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectEfficiencyen_US
dc.subjectFinite element methoden_US
dc.subjectWireless power transferen_US
dc.subjectArtificial Neural Network (ANN)en_US
dc.titleUsing artificial neural networks to improve the efficiency of transformers used in wireless power transmission systems for different coil positionsen_US
dc.titleUsing artificial neural networks to improve the efficiency of transformers used in wireless power transmission systems for different coil positions
dc.typeArticleen_US

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