| Title |
Multi-Objective Optimum Design of Premium High Efficiency Induction Motor Using Parameter Learning |
| Authors |
김민석(Min-Seok Kim) ; 김창업(Chang-Eob Kim) |
| DOI |
https://doi.org/10.5370/KIEE.2021.70.7.991 |
| Keywords |
Premium high efficiency induction motor; Design optimization; Multi-objective optimization; Global Response Surface Method |
| Abstract |
In this paper, the optimum design of a 3.7kW premium high-efficiency induction motor was proposed for reducing the cost using a low-grade iron core while maintaining the efficiency of the motor using a high-grade iron core. Global Response Surface Method(GRSM), one of the multi-objective optimization techniques, was used to satisfy the multi-objective optimization such as complex design problems with cost and production ranges. And GRSM performs the parallel analysis for accurate and efficient optimization search, including local and global search functions. In addition, the commercial optimization program HyperStudy and the electromagnetic FEM solver were used for the characteristic analysis of the motor. As a result of optimization, the price of optimum model was decreased 8% compared with the base model. The reliability of the proposed method was verified by the experiment. |