Optimization of permanent magnet synchronous machines using genetic algorithms – running

A current trend in the automotive industry is the growing interest in electric powertrains. Due to their high power and torque density, permanent magnet synchronous machines are playing a prominent role in the development of the industry. Increasing demands also require continuous improvement and modernisation of design processes. The application of methodologies from different disciplines, such as genetic algorithms, can help to increase the efficiency and accuracy of the design and optimisation process, while reducing the runtime.
During the design process, it is essential to check the expected results of the analytical engine model based on the equations using finite element method electromagnetic field calculation software.
The time required to run the genetic algorithm increases significantly with the number of populations and generations, making development a resource-intensive task.
My research would benefit greatly if I could use the cluster to run the genetic algorithms I have developed, supported by finite element computation, on larger numbers of sample. The results would be used for a TDK thesis and later for a diploma thesis.

Project owner:
Nagy Nándor Sándor (Villamos Energetika Tanszék)
Villamos Energetika Tanszék (VIK-VET)

Tanszéki konzulens: Janka Sándor, főtanácsos
Külső konzulens: Vörös Gábor, Robert Bosch Kft.