Abstract
This paper proposes a statistical probability approach to evaluate the quality loss function of electromagnetic design problems, which is expressed in terms of the first two statistical moments, mean and variance. A univariate dimension reduction method is employed to calculate the statistical moments of a performance function and their sensitivities accurately, and efficiently. Finally, the method is integrated into the robust design optimization algorithm. The proposed method explores an optimum design with statistical information so that it can provide a more accurate solution than other robust design methods. The proposed method is tested with a mathematical model and a blushless DC motor, and its numerical accuracy and efficiency are examined by comparison with existing methods.
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