Isogeometric Methods for the Simulation and Optimization of Electric Motors

02 Mai 2024
Aula Magna da Facultade de Matemáticas (USC) e online

"Isogeometric Methods for the Simulation and Optimization of Electric Motors", organizado por CITMAga. Será impartido por Melina Merkel. Group of Computational Electromagnetics, Technical University of Darmstadt.

Data: 2 de maio de 2024.

Hora: 10:00 h.

Duración: 1 hora

Lugar: Aula Magna da Facultade de Matemáticas (USC) e online por MS Teams a través do enlace Teams Meeting.


The rise of e-mobility due to the transition towards sustainable energy use has underscored the importance of optimizing electric motors. For electric vehicles to be feasible considering battery life and energy consumption in general, the used motors have to be optimized. Machine simulation has traditionally relied on the finite element method, with the rotation of the machine typically achieved using 'locked step', 'sliding surface', 'moving band' and 'harmonic coupling' approaches.
However, 'sliding' methods may encounter issues with geometric mismatch at the interface, which can lead to numerical noise. We employ isogeometric mortaring to circumvent these problems. One problem in 3D magnetostatic simulations using a magnetic vector potential approach is the non-uniqueness of the solution.
This problem is solved by applying a tree-cotree decomposition to remove the discrete kernel of the system. We propose the application of tree-cotree gauging to isogeometric mortaring and investigate the convergence of the obtained formulation.
Finally, an optimization method is introduced, based on shape calculus.
Shape sensitivity analysis is used to determine the shape derivative of the objective functional, i.e., the total harmonic distortion (THD) of the electromotive force. This method allows for a freeform shape optimization which is not restricted by the choice of a set of optimization parameters. This freeform shape optimization is applied to an isogeometric model of a rotating permanent magnet synchronous machine, minimizing the THD, where a reduction of 75% is achieved.