In-system IGBT power loss behavioral modeling

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 modeled, 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

Analysis of Dynamic Wireless Power Transfer Systems Based on Behavioral Modeling of Mutual Inductance

“…compares the predictions of M tx1,bhv and M tot,bhv (dotted lines) to the corresponding FEM-based data (square markers), for the case #2 VDS trajectory. The plots ofFigures 5 and 6confirm the good accuracy and the generalization capability of the behavioral model given in Equations (10)-(12).…”

“…Coefficient values for the behavioral model given in (11). The plots of Figure 5 show the total mutual inductance M tot obtained by combining the formulas given in Equations (10)- (12), for the TDS trajectories of case #1.…”

“…In this paper, we follow the second approach, by deriving, validating and using an analytical behavioral model of M. This modeling approach has been previously used to assess the losses and performances in power devices and power modules, like IGBTs [12], inductors [13], and inverter modules [14], and to study static WPTSs [15]. Compared to the static condition analyzed in [15], the dynamic problem analyzed herein introduces new challenges and features, related to the geometry and to the time-domain behavior.…”

Mutual Inductance Behavioral Modeling for Wireless Power Transfer System Coils

“…In this paper, we present a possible solution to these issues, based on a computation approach combining electromagnetic 3D-FEM numerical solvers and Multi-Objective Genetic Programming (MOGP) evolutionary algorithm [9]. The MOGP algorithm was previously used for discovering power loss behavioral models of IGBTs, power inductors and inverter power modules [10]- [12]. The proposed approach uses 3D-FEM solvers to calculate only the mutual inductance over a limited small set of coils geometrical misalignment parameters (axial, lateral and rotational), and provide data sets to the MOGP algorithm generating analytical expressions of the mutual inductance as a function of misalignment parameters.…”