Acoustic Noise Mitigation of Switched Reluctance Machines with Windows on Stator and Rotor Poles

Author(s):  
Omer Gundogmus ◽  
Mohammed Elamin ◽  
Yusuf Yasa ◽  
Tausif Husain ◽  
Yilmaz Sozer ◽  
...  
Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1161 ◽  
Author(s):  
Pere Andrada ◽  
Balduí Blanqué ◽  
Eusebi Martínez ◽  
José Ignacio Perat ◽  
José Antonio Sánchez ◽  
...  

Nowadays, there is a renewed interest in switched reluctance machines and especially in axial-flux switched reluctance machines (AFSRM). This paper presents a comprehensive design procedure for modular AFSRM with an inner stator and two exterior rotors that have a new distribution of the stator and rotor poles, resulting in short magnetic paths with no flux reversal. After a description of the proposed machine, the output torque equation is derived from a simplified non-linear energy conversion loop and guidelines for its design are given. Once the preliminary sizing has been carried out the different modules of the AFSRM, the magnetically active parts made with SMC, are reshaped or refined using 3D printing and 3D electromagnetic finite element analysis until they reach their definitive shape and dimensions. Finally, an AFSRM has been built following the proposed design procedure and has been validated by experimental measurements.


2013 ◽  
Vol 313-314 ◽  
pp. 45-50 ◽  
Author(s):  
Mohammadali Abbasian ◽  
Vahid Hanaeinejad

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.


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