TU Darmstadt / ULB / TUprints

Robust Design Optimization of Electric Machines with Isogeometric Analysis

Komann, Theodor ; Wiesheu, Michael ; Ulbrich, Stefan ; Schöps, Sebastian (2024)
Robust Design Optimization of Electric Machines with Isogeometric Analysis.
In: Mathematics, 2024, 12 (9)
doi: 10.26083/tuprints-00027335
Article, Secondary publication, Publisher's Version

[img] Text
Copyright Information: CC BY 4.0 International - Creative Commons, Attribution.

Download (1MB)
Item Type: Article
Type of entry: Secondary publication
Title: Robust Design Optimization of Electric Machines with Isogeometric Analysis
Language: English
Date: 13 May 2024
Place of Publication: Darmstadt
Year of primary publication: 25 April 2024
Place of primary publication: Basel
Publisher: MDPI
Journal or Publication Title: Mathematics
Volume of the journal: 12
Issue Number: 9
Collation: 18 Seiten
DOI: 10.26083/tuprints-00027335
Corresponding Links:
Origin: Secondary publication DeepGreen

In electric machine design, efficient methods for the optimization of the geometry and associated parameters are essential. Nowadays, it is necessary to address the uncertainty caused by manufacturing or material tolerances. This work presents a robust optimization strategy to address uncertainty in the design of a three-phase, six-pole permanent magnet synchronous motor (PMSM). The geometry is constructed in a two-dimensional framework within MATLAB®, employing isogeometric analysis (IGA) to enable flexible shape optimization. The main contributions of this research are twofold. First, we integrate shape optimization with parameter optimization to enhance the performance of PMSM designs. Second, we use robust optimization, which creates a min–max problem, to ensure that the motor maintains its performance when facing uncertainties. To solve this bilevel problem, we work with the maximal value functions of the lower-level maximization problems and apply a version of Danskin’s theorem for the computation of generalized derivatives. Additionally, the adjoint method is employed to efficiently solve the lower-level problems with gradient-based optimization. The paper concludes by presenting numerical results showcasing the efficacy of the proposed robust optimization framework. The results indicate that the optimized PMSM designs not only perform competitively compared to their non-robust counterparts but also show resilience to operational and manufacturing uncertainties, making them attractive for industrial applications.

Uncontrolled Keywords: robust PDE constrained design optimization, isogeometric analysis, electrical machines, bilevel optimization
Identification Number: Artikel-ID: 1299
Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-273352
Additional Information:

This article belongs to the Special Issue Numerical Optimization for Electromagnetic Problems

Classification DDC: 500 Science and mathematics > 510 Mathematics
600 Technology, medicine, applied sciences > 621.3 Electrical engineering, electronics
Divisions: 18 Department of Electrical Engineering and Information Technology > Institute for Accelerator Science and Electromagnetic Fields > Computational Electromagnetics
04 Department of Mathematics > Optimization
Date Deposited: 13 May 2024 13:33
Last Modified: 13 May 2024 13:33
SWORD Depositor: Deep Green
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/27335
Actions (login required)
View Item View Item