Methods and algorithms for power devices losses behavioral modeling

2015 - 2016Power electronics is since decades in the focus of very important technology innovations, as the characteristics and the performances of power supplies can severely condition and limit the performances of the system to be fed. In almost all the applications there is the demand to increase as much as possible the ratio between the maximum power the power supplies can deliver and their volume, defined as the power-density while, at the same time, the cost must be as reduced as possible. For this reason, electronic system designers have the task of finding, in a reasonable time, ever better performing solutions, choosing the best semiconductor devices and magnetic components. The attention of this thesis has been on the modeling of power losses of magnetic components and semiconductor devices, considering that they have the biggest impact on the system efficiency. The model classically adopted are usually calculated in different conditions from the operative conditions, require long time simulations, need the knowledge input variables that cannot be easily measured and have coefficients difficult to be identified. For this reason, the aim of this thesis has been to investigate a general approach to identify power losses models of devices, obtained from experimental data. In particular, sufficiently accurate and at the same time simple and intelligible loss model are desired. The approach adopted is based on Genetic Programming (GP), that is an evolutionary method able to return output models, in order to minimize a given fitness function that is a metric of the quality of the solution. The goal of the algorithm has been to obtain models accurate, but at the same time simple and intelligible for the user. These two desired conditions are often conflicting, being complicated models usually accurate and simple models usually inaccurate. For this reason, a Multi Objective (MO) approach, returning a Pareto Front composed non-dominated solutions, has been adopted. Moreover, the GP has been modified to return parametric functions, having the same structure, but different coefficients for all the devices to characterize. In this way, it is supposed to have a more general model, that is sufficiently good for all the devices. ... [edited by Author]XXIX cicl

A genetic programming approach to modeling power losses of Insulate Gate Bipolar Transistors

In high-power-density power electronics application, it's important to be able to predict the power losses of semiconductor devices in order to maximize global system efficiency and to avoid thermal damages of the components. In this paper a novel approach to model the power losses of Insulate Gate Bipolar Transistors (IGBT) in Induction Cooking (IC) application is proposed. The inherent lack of precise physical IGBT loss model and the uncertainty of load in IC application has stimulated the idea to identify system-level behavioral power loss models that allow to cover a variety of devices and load conditions. For this goal, a Genetic Programming approach has been adopted, that starts from measured electrical quantities and returns a set of models, each one with the same structure but with different parameters relevant to the device under test. The models generated by the proposed method based on a training set of case studies have been merged into a generalized model and verified through a validation set

In-system IGBT power loss behavioral modeling

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

Minimum computing adaptive MPPT control

This paper discusses an adaptive Maximum Power Point Tracking (MPPT) control involving minimum computing effort, suitable for implementation with low cost microcontrollers. The runtime multiple optimal setup of the Perturb&Observe MPPT algorithm, is achieved by exploiting the correlation existing among the MPPT efficiency and the onset of a permanent 3 level quantized oscillation around the MPP. As no operations on measured voltage, current and power are required, the adaptive MPPT control is achievable with very cheap digital devices. Experimental test results are presented in the paper, regarding a 70W LED lighting system fed by a photovoltaic source, including a energy storage device

Genetic programming approach for identification of ferrite inductors power loss models

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 behavioral models obtained by means of the GP approach are in good agreement with experimental measurements

Intensification of a flat-plate photocatalytic reactor performances by innovative visible light modulation techniques: A proof of concept

This paper investigates the effect of controlled periodic illumination by visible LEDs on the performances of a flat-plate photocatalytic reactor for wastewater treatment. Different LED dimming techniques are investigated and compared, including the classical Pulse Width Modulation (PWM) technique and a novel proposed VariablePeak PWM technique. A modulation of dimming duty-cycle is adopted as well, which allows to control the light irradiation in a new way with respect to previously used methods. Experimental results highlight the improvement in the photocatalytic degradation process obtained by using the proposed modulation techniques

Photocatalytic reactor with multiphase digital control of luminous radiation

This paper investigates the effect of controlled periodic illumination by visible LEDs on the performances of a visible-light-active N-doped TiO2 photocatalyst (N - TiO2) immobilized on glass spheres for wastewater treatment, using Methylene Blue (MB) dye as a model pollutant. Different LED dimming techniques are investigated and compared, including a classical Pulse Width Modulation (PWM) technique and a novel proposed Variable-Peak PWM technique. A modulation of dimming duty-cycle is adopted as well, which allows to control the light irradiation in a new way with respect to previously used methods. Experimental results highlight the improvement in MB photocatalytic degradation process obtained by using the proposed modulation techniques