Marie-Ange Raulet

Identification of Jiles–Atherton Model Parameters Using Particle Swarm Optimization

This paper presents the use of the multiobjective particle swarm optimization (PSO) technique for the identification of Jiles-Atherton model parameters. This approach, implemented for the first time in order to solve this kind of problem, is tested for two magnetic materials: NO 3% SiFe and NiFe 20-80. The results are compared with those obtained with a direct search method and a genetic algorithm procedure. Experimental measures performed on both samples of materials allow us to complete and argue the validation for the PSO method.

The magnetic field diffusion equation including dynamic hysteresis: a linear formulation of the problem

The introduction of accurate material modeling such as hysteresis phenomenon in numerical field calculation leads to numerical problems induced by the nonlinear properties of the initial system. We focus on the solution of the magnetic field diffusion equation, which contains such problems. This paper presents a new formulation of the diffusion equation including dynamic hysteresis. The resulting formulation leads to a linear system to solve. A numerical implementation of the problem and an experimental validation are also presented.

Magnetic Behavior Representation Taking Into Account the Temperature of a Magnetic Nanocrystalline Material

The aim of this study consists in modeling the magnetic behavior of a nanocrystalline material, taking into account temperature variation. Indeed the development of power electronic embedded systems leads to increase the operating temperature range. Besides nanocrystalline material is used more and more in such systems, so temperature influence is a key point in the magnetic component design.

Dynamical Models for Eddy Current in Ferromagnetic Cores Introduced in an FE-Tuned Magnetic Equivalent Circuit of an Electromagnetic Relay

Electromagnetic relay modeling is elaborated using a magnetic equivalent circuit (MEC). The lumped parameters of the MEC are fitted with respect to 3-D finite-element simulation by using classical optimization algorithms. An accurate dynamic material law has to be taken into account in the modeling, considering the massive core of the circuit. Two accurate dynamical models for representing eddy currents are studied. The simulation of the relay is carried out for several excitation frequencies. A comparison between measurements and simulated quantities is provided.

Power Loss Prediction and Precise Modeling of Magnetic Powder Components in DC–DC Power Converter Application

In power electronics applications, magnetic components are often subjected to nonsinusoidal waveforms, variable frequencies, and dc bias conditions. These operating conditions generate different losses in the core compared to sinusoidal losses provided by manufacturers. In the conception and design stage, lack of precise losses diagnosis has unacceptable effects on systems efficiency, reliability, and power consumption. Since virtual prototyping is used to predict and improve systems behavior before realization, losses and behavior prediction of components is possible. Circuit simulators and their compatible components models are required. This paper is summarized by proposing nonlinear dynamic model of powdered material magnetic core for use in circuit simulators. It includes the materials nonlinear hysteresis behavior with accurate winding and core modeling. The magnetic component model is implemented in circuit simulation software “Simplorer” using VHDL-AMS modeling language. Waveforms and losses of a powder core inductor in a buck converter application are simulated and compared to measured ones. The model is validated for different ripple currents, different loads, and a wide frequency range. DC bias is taken into account in both continuous and discontinuous conduction modes.

A Comparative Study: Dynamic and Thermal Behavior of Nanocrystalline and Powder Magnetic Materials in a Power Converter Application

In the design of such power electronics applications as power converters, lack of precise characterization and diagnosis of losses from components has unacceptable effects on efficiency, reliability, and power consumption. Because passive components, especially magnetic components, are crucially important in power converters, accurate characterization and modeling of magnetic materials is mandatory, to enable realistic prediction of their behavior under variable operating conditions. Temperature is one such condition that induces major changes in a component’s behavior by modifying the material’s magnetic properties. In the work discussed in this paper we investigated the magnetic and thermal behavior of nanocrystalline and powder materials in a DC–DC converter application. Core loss measurements under variable conditions were performed on toroid-shaped samples. Measured results were analyzed for different frequencies, flux densities, and temperatures.

Temperature-Dependent Extension of a Static Hysteresis Model

Some soft magnetic materials are strongly dependent on the temperature, because of their low Curie temperature. In order to predict their behavior in electrical devices, engineers need hysteresis models able to consider the temperature. This paper is an attempt to consider the temperature in an existing model of static hysteresis through its parameters. Variations of some parameters with temperature are issued or build thanks to the literature. At the end, all needed parameters have an analytical law versus temperature. The simulation results are compared with measurements and discussed.

Modélisation des pertes et du cycle d'hystérésis dynamique des tôles

This paper gives the main results obtained in the frame of GDR « SDSE » group work on magnetic materials modeling. The models presented allow magnetic losses or hysteresis loops to be predicted for variable frequency and waveform excitation. A systematic comparison with experiment is done in order to analyze the models capabilities.