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http://dx.doi.org/10.5370/JEET.2018.13.6.2262

Robust Optimization with Static Analysis Assisted Technique for Design of Electric Machine  

Lee, Jae-Gil (Dept. of Electrical and Computer Engineering, Seoul National University)
Jung, Hyun-Kyo (Dept. of Electrical and Computer Engineering, Seoul National University)
Woo, Dong-Kyun (Dept. of Electrical Engineering, Yeungnam University)
Publication Information
Journal of Electrical Engineering and Technology / v.13, no.6, 2018 , pp. 2262-2267 More about this Journal
Abstract
In electric machine design, there is a large computation cost for finite element analyses (FEA) when analyzing nonlinear characteristics in the machine Therefore, for the optimal design of an electric machine, designers commonly use an optimization algorithm capable of excellent convergence performance. However, robustness consideration, as this factor can guarantee machine performances capabilities within design uncertainties such as the manufacturing tolerance or external perturbations, is essential during the machine design process. Moreover, additional FEA is required to search robust optimum. To address this issue, this paper proposes a computationally efficient robust optimization algorithm. To reduce the computational burden of the FEA, the proposed algorithm employs a useful technique which termed static analysis assisted technique (SAAT). The proposed method is verified via the effective robust optimal design of electric machine to reduce cogging torque at a reasonable computational cost.
Keywords
Cogging torque reduction; Electric machine; Optimal design; Robust optimization;
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