In-system IGBT power loss behavioral modeling

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@InProceedings{Femia:2016:SMACD,

• author = "N. Femia and M. Migliaro and C. Pastore and D. Toledo",
• booktitle = "2016 13th International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design (SMACD)",
• title = "In-system IGBT power loss behavioral modeling",
• year = "2016",
• abstract = "In high-power-density power electronics applications, it is important to predict the power losses of semiconductor devices in order to maximize global system efficiency and avoid thermal damages of the components. When different effects influence the power losses, some of which difficult to be physically modelled, it is worthwhile to use empirical laws obtained starting from experimental data, like the Steinmetz's equation widely used for inductors' magnetic core losses prediction. This paper discusses a method to find empirical power loss models by using Genetic Programming (GP). In particular, the GP approach has been applied to identify power losses in Insulated Gate Bipolar Transistors for Induction Cooking application. A loss model has been obtained using an experimental training set, and the result has been successively validated.",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/SMACD.2016.7520723",
• month = jun,
• notes = "Also known as \cite{7520723}",

}

Genetic Programming entries for Nicola Femia Mario Migliaro Cristiano Pastore Davide Toledo

Citations