Uncertainty Quantification and Sensitivity Analysis in a Nonlinear Finite-Element Model of a Permanent Magnet Synchronous Machine

被引：15

作者：

Beltran-Pulido, Andres ^{[1
]}

Aliprantis, Dionysios ^{[1
]}

Bilionis, Ilias ^{[2
]}

Munoz, Alfredo R. ^{[3
]}

Leonardi, Franco ^{[3
]}

Avery, Seth M. ^{[3
]}

机构：

[1] Purdue Univ, Sch Elect & Comp Engn, W Lafayette, IN 47907 USA

[2] Purdue Univ, Sch Mech Engn, W Lafayette, IN 47907 USA

[3] Ford Motor Co, Dearborn, MI 48121 USA

来源：

IEEE TRANSACTIONS ON ENERGY CONVERSION | 2020年 / 35卷 / 04期

关键词：

Finite element analysis; Steel; Uncertainty; Computational modeling; Rotors; Lamination; Punching; Finite-element analysis; Gaussian processes; permanent magnet machines; principal component analysis; sensitivity analysis; uncertain systems; COGGING TORQUE;

D O I：

10.1109/TEC.2020.3001914

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

The objective of this article is to set forth a computationally efficient methodology to quantify the effects and assess the relevance of geometric and material uncertainty on a permanent magnet synchronous machine (PMSM), based on a nonlinear finite-element model (FEM). Our methodology follows the theory of Gaussian process regression and principal component analysis to build a computationally inexpensive surrogate model that replaces the FEM. Uncertainty quantification and sensitivity analysis studies focus on the electromagnetic torque, flux linkage, and core loss of the PMSM.

引用

页码：2152 / 2161

页数：10

共 35 条

[1] ON THE CONDITION NUMBER OF COVARIANCE MATRICES IN KRIGING, ESTIMATION, AND SIMULATION OF RANDOM-FIELDS [J].