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Energies 2017, 10(12), 1962; doi:10.3390/en10121962

A Review of Design Optimization Methods for Electrical Machines

1
School of Electrical and Data Engineering, University of Technology Sydney, Ultimo 2007, Australia
2
State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300131, China
*
Author to whom correspondence should be addressed.
Received: 30 September 2017 / Revised: 21 November 2017 / Accepted: 22 November 2017 / Published: 24 November 2017
(This article belongs to the Section Energy Fundamentals and Conversion)
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Abstract

Electrical machines are the hearts of many appliances, industrial equipment and systems. In the context of global sustainability, they must fulfill various requirements, not only physically and technologically but also environmentally. Therefore, their design optimization process becomes more and more complex as more engineering disciplines/domains and constraints are involved, such as electromagnetics, structural mechanics and heat transfer. This paper aims to present a review of the design optimization methods for electrical machines, including design analysis methods and models, optimization models, algorithms and methods/strategies. Several efficient optimization methods/strategies are highlighted with comments, including surrogate-model based and multi-level optimization methods. In addition, two promising and challenging topics in both academic and industrial communities are discussed, and two novel optimization methods are introduced for advanced design optimization of electrical machines. First, a system-level design optimization method is introduced for the development of advanced electric drive systems. Second, a robust design optimization method based on the design for six-sigma technique is introduced for high-quality manufacturing of electrical machines in production. Meanwhile, a proposal is presented for the development of a robust design optimization service based on industrial big data and cloud computing services. Finally, five future directions are proposed, including smart design optimization method for future intelligent design and production of electrical machines. View Full-Text
Keywords: electrical machines; multi-level optimization; multi-objective optimization; system-level optimization; manufacturing variations; manufacturing quality; robust optimization; industrial big data; cloud computing electrical machines; multi-level optimization; multi-objective optimization; system-level optimization; manufacturing variations; manufacturing quality; robust optimization; industrial big data; cloud computing
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Lei, G.; Zhu, J.; Guo, Y.; Liu, C.; Ma, B. A Review of Design Optimization Methods for Electrical Machines. Energies 2017, 10, 1962.

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