Recent Design Optimization Methods for Energy-Efficient Electric Motors and Derived Requirements for a New Improved Method—Part 2

• Main Authors: Johannes Schmelcher, Max Kleine Büning, Kai Kreisköther, Dieter Gerling, Achim Kampker
• Format: Article
• Language: English
• Published: MDPI AG 2018-10-01
• Series: Proceedings
• Subjects: electric motor; design optimization; deterministic methods; stochastic methods; physical models; surrogate models; energy-efficient motors; boundary conditions
• Online Access: https://www.mdpi.com/2504-3900/2/22/1401

Designing energy-efficient electric motor is a task where multiple goals have to be achieved at once. To find the best design possible, different approaches have been developed. In part one of this multipart paper, the characteristics of the design optimization problem and methods to solve them have been presented. Part two will deal with the different types of model descriptions and how the fundamental workflows look like. The third and last paper will evaluate the findings concerning the solution methods of the design optimization problem of electric motors. As a consequence, requirements for a new improved optimization method are deduced and presented.