4.8 Article

Modern Electrical Machine Design Optimization: Techniques, Trends, and Best Practices

期刊

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
卷 65, 期 10, 页码 7672-7684

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIE.2018.2801805

关键词

Electric machines; evolutionary computation; genetic algorithms (GAs); metamodeling; multidimensional systems; optimization; Pareto optimization; particle swarm optimization (PSO); reliability; robustness

资金

  1. Linz Center of Mechatronics (LCM)-K2 Center for Symbiotic Mechatronics

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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.

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