Artificial intelligence-based rotor position estimation for a 6/4 pole switched reluctance machine from phase inductance

Author(s):  
D. Susitra ◽  
S. Paramasivam
2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Zhengyuan Gao ◽  
Shanming Wang ◽  
Zhiguo An ◽  
Pengfei Sun

Considerable vibration and acoustic noise limit the further application of Switched Reluctance Machine (SRM) due to its structural characteristics and working principle. An improved SRM model with double auxiliary slots (DAS) was proposed, in which the direction of the magnetic line of force was adjusted, and the radial magnetic density in the air gap was reduced by changing the local tooth profiles of the stator and the rotor. The effects of initial rotor position and turn-on angle and turn-off angle on radial Electromagnetic Force (EMF) and maximum torque were investigated. The results indicate the radial EMF and torque increase significantly with the advancement of the turn-on angle or the delay of the turn-off angle. In the orthogonal experimental design, initial rotor position, turn-on angle, and turn-off angle were taken as the factors, and the optimal set of parameters that minimized radial EMF was determined according to a greater output torque. In contrast to conventional SRM, the radial EMF of the SRM with DAS significantly reduces when the optimal set is applied.


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