In-system IGBT power loss behavioral modeling

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@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