Torque Optimization of Double-Stator Switched Reluctance Machine

Abstract:

Double-stator switched reluctance machines benefit from a high torque density and a low radial force level in comparison with conventional switched reluctance machines resulting in a lower vibration and acoustic noise. Therefore, they are suitable candidate for automotive applications. However, torque pulsation which is also a source for vibration is still remained and should be alleviate by dimension optimization of the machine. This paper presents a design optimization of a double-stator switched reluctance machine for improving the magnetic torque quality of the machine. For this purpose finite element method along with response surface methodology is used to optimize three parameters of the machine to maximize torque quality factor i.e. the average torque to torque ripple ratio in the machine. Genetic algorithm method is also employed as an optimization tool. The aim of optimization is to maximize the ratio of average torque to torque ripple. Finite element results are presented to verify the optimization method.

• Periodical: Applied Mechanics and Materials (Volumes 313-314)
• Pages: 45-50
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.313-314.45
• Online since: March 2013
• Authors: Mohammadali Abbasian, Vahid Hanaeinejad
• Keywords: Average Torque, Double-Stator, Finite Element Method (FEM), Genetic Algorithm (GA), Optimization, Response Surface Methodology (RSM), Switched Reluctance Machine, Torque Quality Factor, Torque Ripple

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