A Review of Design Optimization Methods for Electrical Machines

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.

Robust Design of a Low-Cost Permanent Magnet Motor with Soft Magnetic Composite Cores Considering the Manufacturing Process and Tolerances

“…DFSS is a popular robust design method and has been successfully employed for the robust design optimization of PM-SMC motors [25,26,32,33]. The following conclusions can be drawn from the table and figures.…”

“…In general, to improve the performance of electrical machines, many optimization methods can be employed, such as the intelligent optimization algorithms, multilevel, multiobjective and multidisciplinary optimization methods [25][26][27][28][29][30][31][32][33]. For the optimization of the investigated FSPMM under manufacturing variations, this is a kind of robust design optimization problem.…”

“…For the optimization of the investigated FSPMM under manufacturing variations, this is a kind of robust design optimization problem. To solve this problem, Taguchi parameter design, worst case design and design for six-sigma (DFSS) are three normally used methods [26,[32][33][34][35][36][37][38]. Among them, Taguchi parameter design method requires the least simulation cost.…”

Analysis and Design of a Compound-Structure Permanent-Magnet Motor for Hybrid Electric Vehicles

“…This can choose a proper working mode during operation, which is regarded as an advantage of HEVs. However, when the magnetic field is supersaturated, it will change the inductance parameters and increase iron losses, lead to the back EMF or current waveform distortion, which produces torque ripple and weakens output torque [13]. Therefore, the electromagnetic structure of CSPM motor needs to be optimized using mathematical model and electromagnetic analysis method in the next part, to realize the magnetic field decoupling of DRM and SM.…”

Design, Analysis and Model Predictive Control of an Axial Field Switched-Flux Permanent Magnet Machine for Electric Vehicle/Hybrid Electric Vehicle Applications

“…Recently, many alternatives such as surrogate-assisted model [27] which emulates the behavior of the real machine performance, is less accurate but much faster, have also been emerged to improve the optimization efficiency of electrical machines, especially for those machines with 3-D flux topologies which requires 3-D FEM, such as the transverse and axial flux as well as claw pole machine. The characteristics of several optimization design models, methods and strategies for electrical machine are summarized and analyzed in [28].…”