Título
Evolution of classical 1-D based models and improved approach for the characterization of litz wire lossesFecha de publicación
2024Grupo de investigación
Sistemas electrónicos de potencia aplicados al control de la energía eléctricaOtras instituciones
Technical University of DenmarkVersión
PostprintTipo de documento
ArtículoArtículoIdioma
engDerechos
© 2024 IEEEAcceso
Acceso abiertoVersión de la editorial
https://doi.org/10.1109/TPEL.2024.3446962Publicado en
IEEE Transactions on Power Electronics Vol. 39. N. 12. Pp. 16371-16381. December, 2024Primera página
16371Última página
16381Editorial
IEEEPalabras clave
High-frequency transformersMathematical model
Wire
ODS 7 Energía asequible y no contaminante
Materia (Tesauro UNESCO)
http://vocabularies.unesco.org/thesaurus/concept621Clasificación UNESCO
Ingeniería y tecnología eléctricasResumen
Prediction of Litz wire losses is a challenging endeavor in the design of high-frequency transformers. Although many analytical approaches of varying complexity can be found in the literature, classic ... [+]
Prediction of Litz wire losses is a challenging endeavor in the design of high-frequency transformers. Although many analytical approaches of varying complexity can be found in the literature, classical 1-D-based models are the norm in the analysis of wide design spaces. Even then, an important degree of uncertainty exists around the accuracy of the 1-D models. After a critical review of these models and an analysis of their application in Litz wire loss prediction, a new model is proposed, which tries to address some of the concerns and limitations of the existing approaches. The models are evaluated against 2-D finite-element simulations in many different conditions to ensure that the models correctly consider the impact of different parameters. The experimental results are presented to demonstrate the accuracy of the new approach at very high frequencies and high amounts of strands using four prototypes with different Litz wires, designed to correctly match the conditions inherent to any 1-D model. [-]
Financiador
Gobierno VascoPrograma
Programa Predoctoral de Formación de Personal Investigador No DoctorNúmero
PRE_2020_1_0267URI de la ayuda
Sin informaciónProyecto
Sin informaciónColecciones
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