An Optimization Framework for Minimizing Cogging Torque in Surface Mounted Permanent Magnet Machines

被引：2
|
作者：
Poudel, Bikrant [1 ]
Amiri, Ebrahim [1 ]
机构：
[1] Univ New Orleans, New Orleans, LA 70148 USA
来源：
2022 IEEE 31ST INTERNATIONAL SYMPOSIUM ON INDUSTRIAL ELECTRONICS (ISIE) | 2022年
关键词：
Analytical modeling; Cogging torque; Permanent magnet machine; Optimization; MOTORS;
D O I：
10.1109/ISIE51582.2022.9831477
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
This paper presents a computationally efficient optimization framework for minimizing cogging torque in Surface Mounted Permanent Magnet (SPM) machines. To bypass excessive computational volume of Finite Element (FE) model, objective functions (i.e., airgap PM flux distribution, and cogging torque) are described analytically. Next the analytical equation and constraints are defined for the Genetic Algorithm (GA)-based optimization procedure to determine the optimal value of design parameters (i.e., number of stator slots, number of PM poles, slot opening width, stator slot skewing, and width of rotor PMs). To determine the effectiveness of the presented solution, the no-load performance of the optimized structure is compared against the initial design.
引用
收藏
页码：492 / 498
页数：7
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