شماره ركورد كنفرانس :
5060
عنوان مقاله :
Unccertainty Quantification of Permanent Magnet Motor Using Response Surface Surrogate Model
Author/Authors :
Vahid، Rafiee Center of Excellence on Applied Electromagnetic Systems - School of Electrical and Computer Engineering - College of Engineering University of Tehran Tehran, Iran , Jawad، Faiz Center of Excellence on Applied Electromagnetic Systems - School of Electrical and Computer Engineering - College of Engineering University of Tehran Tehran, Iran
كليدواژه :
Robust design , descriptive Monte Carlo sampling , uncertainty quantification , design for six-sigma , response surface methodology
عنوان كنفرانس :
11th Power Electronics, Drive Systems, and Technologies Conference (PEDSTC)
چكيده فارسي :
فاقد چكيده فارسي
چكيده لاتين :
There is always uncertainty in all aspects of the
real life problems. Deterministic optimizations do not take into
account the tolerance of input parameters and also the
imperfections in operation condition. These uncertainties may
cause failure in product line. To produce a product with the
least possible failure, the uncertainties must be considered in
design and optimization process. This paper presents
deterministic and robust design optimization of an outer rotor
permanent magnet motor. To reduce the computational
burden of finite element method (FEM) application in the
optimization process of motor response surface methodology
(RSM) surrogate model is adopted. The robust optimization of
the motor is based on design for six sigma (DFSS) methodology
and the samples are generated using descriptive Monte Carlo
sampling (MCS). Finally, the deterministic and robust motors
are compared using FEM and the mass production of both
motors is simulated.
