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Recherche, Développement et Innovation en Génie Electrique

Seminar in OMN TEAM

The research team OMN works on different numerical methods associated to electromagnetic field computation. We organize the Junior Seminar in LILLIAD Learning center innovation by our Ph.D. students, as well as our postdocs, and Invited Seminar by the external researchers.

If you would like to give us a talk or have some collaboration ideas about our work, please contact Zuqi who is in charge of the seminar, we can invite you to Lille.
The seminar can be held in English (or French) as you like. There is no limit for the duration of the seminar.

Upcoming seminars:

September 11, 2023, Invited Seminar

Pr. Tetsuji MATSUO (Kyoto University, Japan)

Tetsuji Matsuo received the B.E., M.E., and Dr. Eng. degrees from Kyoto University, Japan, in 1986, 1988 and 1991, respectively. He became a Research Associate, a Lecturer, and an Associate Professor at Kyoto University in 1991, 2001, and 2003, respectively. He is currently a Professor in the Department of Electrical Engineering, the Graduate School of Engineering, Kyoto University. His current research interests include computational electromagnetics and magnetic material modeling.

Physical/Phenomenological Modeling of Magnetic Materials

Many macroscopic models of magnetic materials are constructed phenomenologically, where model parameters are determined from measured magnetic property data. To predict magnetic properties without using measured data, a physical model of magnetic materials is necessary. In this seminar, an energy-based multiscale model called « multi-domain particle model » (MDPM) will be discussed. The MDPM is composed of mesoscopic multi-domain particles, and its magnetization state is determined through the local minimization of the total magnetic energy. The influence of magneto-mechanical interactions is represented by the magnetoelastic energy. The MDPM successfully predicts an increase in hysteresis loss due to mechanical stress without fitting to measured data under mechanical stress conditions. Additionally, depending on the audience’s interest, a phenomenological hysteresis model based on the play model will also be addressed.


Esteban HUSSON (TBD)

Past seminars:

July 11, 2023, Junior Seminar


Development of an approach combining physical modeling and artificial intelligence for modeling the magnetic properties of electrical steels

The energy efficiency of modern motor systems depends on the accuracy and reliability of design tools, particularly those related to electrical steels used in magnetic circuits. However, the mechanical and thermal constraints imposed by manufacturing processes and the use of these motor systems can affect their properties, potentially degrading performance. Traditional approaches to modeling these materials are often complex and slow, while designers need precise and fast models. This thesis proposes integrating Artificial Intelligence (AI), specifically Deep Learning (DL), with multi-physical models of electrical steels to create optimized, faster, and adaptable models for design and optimization procedures. This approach focuses on the development, validation of these models, and their implementation in a numerical calculation code for academic tests.

June 08, 2023, Junior Seminar

Sqalli GHALI

Du matériau à la structure magnétique par fabrication additive

Additive manufacturing is a flexible and efficient process allowing to create complex components at a reduced expense when compared to conventional methods. While it is not yet extensively employed, additive manufacturing holds promise in the field of electrical engineering, especially for the production of intricate and compact parts. The aim of this PhD is to produce soft ferrite magnetic components  with good magnetic properties using additive manufacturing. The research focuses on improving printed materials and taking into account the specific features of printing in the design of new components. One idea is to be able to propose shapes and solutions adapted to the magnetic material and its shaping process through topological optimization tools.

Mohamed Reda Saouthi

Méthodologie de dimensionnement et de supervision énergétique d’un smart grid ferroviaire

The integration of decentralized generation and energy storage systems in railway electrification networks is seen as a solution for improving the electrical and energy performance of rail power grids, which are facing a sharp increase in traffic. The aim of this thesis is to define a methodology for the optimal design and energy management of energy production and storage systems in a railway environment. The architecture must be coupled with the energy management of the system to obtain optimized sizing. several approaches will be taken, the first consisting in the realization of a linear optimization model that will simultaneously optimize the dimensions of system components and energy management, the second approach will rely on finer optimization models integrating the non-linearity that naturally appears in the optimization objectives, functional constraints and behavior laws of system components. several optimization schemes will be tested, starting with nested optimization. Finally, we will quantify the variability of the system’s performance in relation to uncertainties about the production of renewable energies and the power consumed by the rolling machines.

May 04, 2023, Junior Seminar


Résolution numérique de problèmes électromagnétiques non linéaires en présence d’hystérésis et anisotropie

Electrical machines are currently the subject of many researches to improve their efficiency by a few percent. One solution consists in using high performance magnetic materials (sheets). However, it appears that the behavior of these materials is highly nonlinear and anisotropic and also presents hysteresis when used in machines. In order to evaluate precisely the efficiency, before the construction of real prototypes, we use numerical modeling that must take into account the nonlinear character of these materials. The L2EP has been developing, with EDF R&D in the context of LAMEL, for many years a computational code, named code_carmel, based on the finite element method to model electromagnetic devices in low frequency. The objective of this PhD is to add to code_carmel the resolution of nonlinear problems integrating anisotropic and hysterical models.


Characterization and modelling of ferromagnetic material aging for iron losses reduction

« Magnetic aging » refers to the degradation of in-service magnetic properties of Fe-Si steels when submitted to moderate temperatures. This phenomenon is due to the precipitation of carbides or nitrides at electrical machines operation temperatures of less than 200°C. At the microscopic scale, it was determined that precipitates in the range of 100 nm to 1μm in size are the most deleterious for magnetic properties and that only Fe-Si alloys with silicon content lower than 3wt% are prone to magnetic ageing. These low grade Fe-Si steels correspond however to the largest part (73%) of the current market of non-oriented electrical steels, i.e. 9.8 million tons produced in 2019 in the world.  Although only scarce attempts have been made to model the precipitation kinetics in this system, many precipitation modelling methods have been developed in material sciences. It appears that models are nowadays available to describe the time evolution of precipitates in magnetic steels. We can now expect to construct the bridge between microscopic models of precipitation and macroscopic models of the magnetic behavior in order to be able to predict this « magnetic aging ». Integrated to the design process, it will allow to better predict the losses, leading to more efficient and more robust electrical machines. It will also give new opportunities to adapt or develop processes during the manufacturing in order to reduce the aging effect according to the operation mode. The aim of the PhD is to develop multi-physical models based on experimental investigations from the microscopic to macroscopic scales of ageing mechanisms in electrical steels and the consequences on iron losses.

April 06, 2023, Junior Seminar

Zhenxin LI

Improvement of the ODF method for the modeling of the B-H magnetization curves of Grain Oriented Electrical Steels

Grain-Oriented Electrical Steels (GOES) are widely used in transformers to increase energy efficiency while reducing the volume and weight of such transformers. These GOES are characterized by their strong anisotropy, which leads to different magnetic properties (behavior law and iron losses) depending on the strength and the direction of the applied magnetic field to the rolling direction (RD). To describe the anisotropy of the GOES behavior law, the Orientation Distribution Functions (ODF) based approach shows interesting features regarding ease of identification and implementation. However, a significant oscillation issue in this model at low magnetic field exits. It is recently reported that a high-order ODF method can improve the accuracy of the original model. But the high-order ODF model implies an important number of experimental data according to different directions of the applied field to RD (different magnetization angles) to build a model with sufficient accuracy. In addition, the accuracy also depends on how the input magnetization angles are selected between the RD and the transverse direction (TD). In this work, an optimal algorithm for input magnetization angle selection is proposed for the high-order ODF method. To validate the proposed algorithm, 13 magnetization angles have been measured. A comparative study has been conducted based on the original and the high-order ODF models built with the proposed selected magnetization angles. It is shown that the proposed algorithm can reduce the number of experimental data needed for the ODF model while providing an acceptable global error.


Optimal Planar Inductor Design

Magnetic components (transformers and inductors) are essential for the proper functioning of power electronics (EP) converters. Following the emergence of new wide-gap active power components (SiC, GaN), magnetic components now appear to be the technological lock to be unlocked in future years to increase the performance of high-frequency (HF) power converters, in particular in terms of power density and energy efficiency. The aim of this PhD is to work on a new generation of inductance optimized for high current DC/DC HF applications with, potentially, a high level of ripple. This will involve the development of a sizing and optimal design tool dedicated to those next-gen inductors. For this, it will be necessary to control the magnetic and thermal aspects as well as the losses dissipated by those components. They are based on a combination of printed circuit board (PCB) for the windings and high and low permeability materials for the magnetic core, typically ferrite and FeNi powder. PCBs have many advantages from an industrial point of view, particularly in terms of reproducibility and control of parasitic elements. Low permeability materials make it possible to create distributed air gap zones by limiting the effects of expansion of the field lines around the air gap(s) (on the central leg or on the 3 legs of a core of type E in ferrite), the latter inducing significant localized losses in the conductors near the air gaps.

March 08, 2023, Junior Seminar


Capteurs RF MEMS électro-acoustiques passifs et sans fil pour le diagnostic précoce de défauts dans les machines électriques de fortes puissances

Les machines électriques de fortes puissances sont soumises à des contraintes sévères en fonctionnement, afin d’assurer la fiabilité et la continuité d’opération de ces machines, notamment par anticipation des opérations de maintenance et de fonctionnement dégradé si nécessaire, il est primordial de disposer d’informations sur ces contraintes, souvent à l’échelle locale. Par ailleurs, obtenir ces informations au niveau du rotor est le moyen le plus sûr pour assurer une surveillance et un diagnostic robustes et fiables.
Seules les technologies de capteurs sans fil et sans batterie associées à des techniques efficaces d’analyse des données et de traitement des signaux peuvent satisfaire un tel besoin. La technologie des composants SAW, exploitant les ondes acoustiques de surface, permet de concevoir des capteurs sans fil et totalement passifs et permet ainsi de répondre à toutes ces contraintes. De nombreuses grandeurs physiques sont mesurables sur cette même base technologique moyennant une ingénierie avancée du design : température, contraintes mécaniques, champ magnétique.

January 24, 2023, Junior Seminar


Investigations des pertes dans les plateaux et doigts de serrage dans les machines de fortes puissances

Les dispositifs de serrage sont utilisés pour appliquer la pression nécessaire au maintien des tôles du stator dans le cas de machines de grande puissance telles que les grands turbogénérateurs. Les courants dans les enroulements d’extrémité du stator et du rotor induisent des courants de Foucault dans ces pièces de serrage qui sont généralement réalisées en acier magnétique conducteur en raison de contraintes économiques. L’enjeu principal est celui de la connaissance la plus précise possible des pertes engendrées par les courants induits dans les plateaux et doigts de serrage utilisés dans les machines électriques de fortes puissances. Plus spécifiquement, les investigations devront analyser l’effet des différentes composantes du champ magnétique ainsi que leurs effets en fonction des matériaux utilisés pour les dispositifs de serrage. Pour ce faire, une approche combinée expérimentale / numérique sera mise en œuvre.



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