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초록
To obtain accurate results from various probabilistic design optimization applied to electromagnetic devices, the uncertainty in the motor should be first identified correctly. This paper presents an efficient uncertainty identification method by using finite element analysis and experimental data. Kriging surrogate model is employed to reduce the computation and maximum likelihood estimation is used to identify the probability distribution of uncertainty and find its parameters. The proposed method is applied to identify the uncertainties in a surface-mounted permanent magnet synchronous motor that cause the cogging torque.
키워드
Kriging surrogate model; Maximum likelihood estimation; Surface-mounted permanent magnet synchronous motor; Uncertainty identification; Computational electromagnetics; Electromagnets; Interpolation; Permanent magnets; Synchronous motors; Uncertainty analysis; Cogging torque; Electromagnetic devices; Kriging surrogate model; Probabilistic design optimization; Surface mounted permanent magnet synchronous motor; Uncertainty identification; Maximum likelihood estimation
- 제목
- Uncertainty identification method using kriging surrogate model for industrial electromagnetic device
- 저자
- Kim, S.; Lee, S.-G.; Kim, J.-M.; Lee, T.H.; Hong, J.-P.
- 발행일
- 2019-00
- 유형
- Conference Paper
- 저널명
- IET Conference Publications
- 권
- 2019
- 호
- CP753
- 페이지
- 1 ~ 3