Radial Force Characteristics of Switched Reluctance Machine

1999 ◽  
Author(s):  
Neil R. Garrigan ◽  
Albert Storace ◽  
Wen L. Soong ◽  
Thomas A. Lipo ◽  
Charles M. Stephens
Keyword(s):  
Radial Force ◽  
Switched Reluctance Machine ◽  
Switched Reluctance ◽  
Reluctance Machine ◽  
Force Characteristics

Torque Optimization of Double-Stator Switched Reluctance Machine

2013 ◽  
Vol 313-314 ◽  
pp. 45-50 ◽  
Author(s):  
Mohammadali Abbasian ◽  
Vahid Hanaeinejad
Keyword(s):  
Finite Element ◽  
Acoustic Noise ◽  
Optimization Method ◽  
Torque Ripple ◽  
Radial Force ◽  
Switched Reluctance Machine ◽  
Switched Reluctance ◽  
Torque Density ◽  
Reluctance Machine ◽  
Switched Reluctance Machines

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.

scholarly journals Multi-Objective Optimization of Switched Reluctance Machine Design Using Jaya Algorithm (MO-Jaya)

Mathematics ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1107
Author(s):  
Mohamed Afifi ◽  
Hegazy Rezk ◽  
Mohamed Ibrahim ◽  
Mohamed El-Nemr
Keyword(s):  
Optimization Techniques ◽  
Design Parameters ◽  
Jaya Algorithm ◽  
Switched Reluctance Machine ◽  
Nsga Ii ◽  
Switched Reluctance ◽  
Multi Objective ◽  
Reluctance Machine ◽  
Linear Relationships ◽  
Forward Equations

The switched reluctance machine (SRM) design is different from the design of most of other machines. SRM has many design parameters that have non-linear relationships with the performance indices (i.e., average torque, efficiency, and so forth). Hence, it is difficult to design SRM using straight forward equations with iterative methods, which is common for other machines. Optimization techniques are used to overcome this challenge by searching for the best variables values within the search area. In this paper, the optimization of SRM design is achieved using multi-objective Jaya algorithm (MO-Jaya). In the Jaya algorithm, solutions are moved closer to the best solution and away from the worst solution. Hence, a good intensification of the search process is achieved. Moreover, the randomly changed parameters achieve good search diversity. In this paper, it is suggested to also randomly change best and worst solutions. Hence, better diversity is achieved, as indicated from results. The optimization with the MO-Jaya algorithm was made for 8/6 and 6/4 SRM. Objectives used are the average torque, efficiency, and iron weight. The results of MO-Jaya are compared with the results of the non-dominated sorting genetic algorithm (NSGA-II) for the same conditions and constraints. The optimization program is made in Lua programming language and executed by FEMM4.2 software. The results show the success of the approach to achieve better objective values, a broad search, and to introduce a variety of optimal solutions.

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