Genetic programming approach for identification of ferrite inductors power loss models

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@InProceedings{DiCapua:2016:IECON,

• author = "Giulia {Di Capua} and Nicola Femia and Mario Migliaro and Kateryna Stoyka",
• booktitle = "IECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society",
• title = "Genetic programming approach for identification of ferrite inductors power loss models",
• year = "2016",
• pages = "1112--1117",
• abstract = "This paper discusses the identification of power loss models of ferrite core power inductors for high-power-density Switch Mode Power Supplies. A novel method, based on Genetic Programming (GP) approach, is herein proposed. It is aimed at discovering new loss models, starting from experimental measurements and taking into account all the operating conditions, such as switching frequency, inductor current ripple and volt-microsecond product, average and rms inductor current values, even for possible inductor operation in partial saturation. The behavioural models obtained by means of the GP approach are in good agreement with experimental measurements.",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/IECON.2016.7793000",
• month = oct,
• notes = "Also known as \cite{7793000}",

}

Genetic Programming entries for Giulia Di Capua Nicola Femia Mario Migliaro Kateryna Stoyka

Citations