Conference Agenda

This paper proposes a hybrid optimization method combining parameter and topology approaches for the design of interior permanent magnet (IPM) motors, utilizing the dynamic Gabor filter. In this hybrid method, magnet shapes are refined through parameter optimization, while the shapes of the magnetic cores are defined via topology optimization with the dynamic Gabor filter. The optimized design features slit-shaped magnetic cores adjacent to the rotor surface, which meet voltage constraints, and incorporate multi-layered magnetic cores and magnet configurations that enhance torque performance.

This study proposes a framework for multi-physics topology optimization of a synchronous reluctance machine. Body-fitted meshes are used for accurate finite element analysis (FEA) and criteria evaluation. The novelty lies in including the outer boundary of the rotor in the designable domain with non-penetration constraints. The design can thus attach and detach freely from the outer boundary enabling new designs to emerge.

This paper addresses the gradient-based design optimization of the air gap profile of an inductor to minimize proximity-effect losses with both parametric and free-shape approaches. The objective is to minimize the proximity effect losses inside the conductors related to the imaginary part of the coil permeability while keeping the inductance value constant. To do that, the sensitivities of the complex magnetic model are derived using the adjoint method. It is shown that the optimized air gap profile is curved in order to concentrate the flux lines away from the (fixed) conductors. Parametric and free-form approaches are then compared. The implementation uses the open-source finite-element toolbox NGsolve and Mmg meshing library; all the codes are freely available.

This paper presents a method for reconstructing magnetic material using magnetic dot sensitivity analysis. The proposed approach introduces the concept of dot sensitivity, which evaluates changes in the objective function when a ferromagnetic material dot is created in the vacant region. This enables simultaneous topology and shape optimization without the need for an initial shape, providing robust identification of target topologies from magnetic flux density data. The method demonstrates feasibility by reconstructing the cross-sectional area of a cast iron cylinder as a numerical example.

In order to better understand and model the various loss mechanisms that occur in electrical machines during operation, the actual degradation of electrical steel sheets due to cutting, punching, welding etc. is of paramount importance. In this contribution, we present a recently developed inverse scheme being capable to identify locally the degradation of the magnetic steel sheets due to the machining process. In doing so, the objective function, which penalises the difference between the measured and the simulated magnetic flux density, has to be minimised under a constraint defined according to the corresponding partial differential equation model. We use the adjoint method to efficiently obtain the gradients of the objective function with respect to the material parameters. Realistic numerical case studies show promising results.