Journal
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
Volume 65, Issue 10, Pages 7672-7684Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIE.2018.2801805
Keywords
Electric machines; evolutionary computation; genetic algorithms (GAs); metamodeling; multidimensional systems; optimization; Pareto optimization; particle swarm optimization (PSO); reliability; robustness
Categories
Funding
- Linz Center of Mechatronics (LCM)-K2 Center for Symbiotic Mechatronics
Ask authors/readers for more resources
Disruptive innovations in electrical machine design optimization are observed in this paper, motivated by emerging trends. Improvements in mathematics and computer science enable more detailed optimization scenarios that cover evermore aspects of physics. In the past, electrical machine design was equivalent to investigating the electromagnetic performance. Nowadays, thermal, rotor dynamics, power electronics, and control aspects are included. The material and engineering science have introduced new dimensions on the optimization process and impact of manufacturing, and unavoidable tolerances should be considered. Consequently, multifaceted scenarios are analyzed and improvements in numerous fields take effect. This paper is a reference for both academics and practicing engineers regarding recent developments and future trends. It comprises the definition of optimization scenarios regarding geometry specification and goal setting. Moreover, a materials-based perspective and techniques for solving optimization problems are included. Finally, a collection of examples from the literature is presented and two particular scenarios are illustrated in detail.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available