Deployment Of Magnetic Anisotropy For More Efficient Electrical Machines, Modeling And Design.

Universities and Institutes of France
October 31, 2022
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  • Organisation/Company: Laboratoire des systèmes électrotechniques et environnement (LSEE)
  • Research Field: Engineering Mathematics Technology › Materials technology
  • Researcher Profile: First Stage Researcher (R1) Recognised Researcher (R2) Established Researcher (R3) Leading Researcher (R4)
  • Application Deadline: 31/10/2022 00:00 - Europe/Athens
  • Location: France › Béthune
  • Type Of Contract: Temporary
  • Job Status: Full-time
  • Abstract

    For several years, the Laboratoire Systèmes Électriques et Environnement (LSEE) has been conducting research in the area of the characterization and the modeling of electrical steel with a focus on grain oriented electrical steel 1. The particularity of that material is twofold. First, it presents a very high efficiency in terms of core losses compared to regular non oriented electrical steel, which makes it a worthwhile material for the building of embedded electrical motors since it allows a high improvement of their power-weight ratio. Second, it presents a very high anisotropic magnetic behavior, which is very hard to model, and thus to implement in magnetic simulation software.

    Recently, a very promising model that allows to account for any magnetization direction while requiring a very limited amount of experimental data to be fully defined has been developed 2 at the LSEE. The next step is now to implement that model inside a finite element method-based software.

    The group of Computational Electromechanics at Aalto University in Finland specializes in the modeling and simulation of electrical machines as well as the modelling and characterization of the underlying magnetic materials. The Focus of the group is on the usage of these models for the design and analysis of high efficiency electrical machines and related tasks such as condition monitoring and control. The group has its own 2D finite element software and has also access to the open source 3D Elmer software. Besides that, the group has a large electrical machines and drives laboratory with excellent facilities. The computational electromechanics group is leading an eight-years center of excellence funded by the Academy of Finland.

    In the proposed thesis, we aim at investigating the potential of grain oriented electric steel in the construction of more efficient electrical motors for industry applications. For this purpose, the implementation of anisotropic models of magnetic materials are required. The thesis work will focus on this implementation, the simulation and the analysis of a wound field large power synchronous machine and induction machines.

    The thesis will be carried out in close cooperation between the LSEE in France and Aalto University in Finland.

    References

    1 S. Lopez, B. Cassoret, J.-F. Brudny, L. Lefebvre, and J.-N. Vincent, “Grain Oriented Steel Assembly Characterization for the Development of High Efficiency AC Rotating Electrical Machines,” IEEE Transactions on Magnetics, vol. 45, no. 10, pp. 4161–4164, Oct. 2009.

    2 G. C. A. Tolentino, J. V. Leite, M. Rossi, O. Ninet, G. Parent, and J. Blaszkowski, “Modelling of magnetic anisotropy in electrical steel sheet by means of cumulative distribution functions of Gaussians,” IEEE Transactions on Magnetics, pp. 1–1, 2022.

    Direction

    Prof. Anouar Belahcen (Aalto University in Finland)

    Prof. Guillaume Parent (Artois Université in France)

    Funding category: Contrat doctoral

    PHD Country: France

    Offer Requirements Specific Requirements

    Profile and skills required

  • Master's degree in electrical engineering, technical physics, or applied mathematics, with a focus on electromechanics or electromagnetism ;
  • Programming skills, numerical methods, independent working skills.
  • Language

    Good knowledge in English

    Contact Information
  • Organisation/Company: Laboratoire des systèmes électrotechniques et environnement (LSEE)
  • Organisation Type: Other
  • Website: https:// lsee.univ-artois.fr
  • Country: France
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