A Novel AC Power Loss Model for Ferrite Power Inductors

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@Article{Stoyka:2019:ieeePE,

• author = "Kateryna Stoyka and Giulia {Di Capua} and Nicola Femia",
• journal = "IEEE Transactions on Power Electronics",
• title = "A Novel AC Power Loss Model for Ferrite Power Inductors",
• year = "2019",
• volume = "34",
• number = "3",
• pages = "2680--2692",
• abstract = "Recent studies have proved that sustainable saturation operation of Ferrite Power Inductors (FPIs) allows reducing the inductor size and increasing the power density in Switch-Mode Power Supply (SMPS) applications. This paper discusses a new behavioural model for reliable prediction of AC power loss in FPIs, including the effects of saturation. The new model has been identified by means of the Genetic Programming (GP) algorithm combined with a Multi-Objective Optimization (MOO) technique, starting from large sets of power loss experimental measurements. The proposed ac power loss model uses as input variables the voltage and switching frequency imposed to the inductor by the SMPS operation, while the DC inductor current is used as a parameter expressing the impact of saturation. Such quantities can be easily determined for whatever converter topology and in real-world switching operation, thus confirming the readiness and the easiness-to-use of the proposed behavioral model. The results of experimental tests presented in this paper prove the reliability of the power loss predictions, also by correctly accounting for the impact of inductors saturation.",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/TPEL.2018.2848109",
• ISSN = "0885-8993",
• month = mar,
• notes = "Also known as \cite{8386705}",

}

Genetic Programming entries for Kateryna Stoyka Giulia Di Capua Nicola Femia

Citations