Robust design optimization of electrical machines and drive systems for high quality mass production

Abstract

Electrical drive is the heart in many modern appliances, as well as industry equipment and systems. In order to achieve the best design objectives, such as high performance and low material cost, various deterministic optimization methods have been developed for optimal design of electrical machines, power electronic converters, and parameters of control algorithms. On the other hand, the final quality of a motor drive system in mass production depends highly on the manufacturing technology employed and can be greatly affected by essential manufacturing tolerances and unavoidable uncertainties due to material diversity, machining error, and assembling inaccuracy, etc. An aggressively optimized design may be difficult to mass produce and end up with high manufacturing cost and/or high rejection rates. To solve this challenge, a robust design technique called design for six-sigma has been introduced to improve the manufacturing quality of both electrical machines and drive systems based on the multi-disciplinary, multi-level and multi-objective optimization methods. This work aims to show the development of these methods and their applications.