Sensorloser Betrieb eines geschalteten Reluktanzmotors mittels Kalman Filter (Sensorless control of a switched Reluctance Motor using a Kalman Filter)

1998 ◽  
Vol 81 (5) ◽  
pp. 297-308
Author(s):  
A. Brösse ◽  
G. Henneberger
Author(s):  
Dr. Kannan Kaliappan

The main purpose of this project is to develop a sensorless control of the switched reluctance motor. As we know the use of switched reluctance has been increasing .Many industries and all other started switching to the switched reluctance motor ,due to there rugged structure and its capability to withstand harsh environments .In this paper we control the switched reluctance motor by controlling the different blocks in the feed back system in the matlab therefore torque controlled .As the switched reluctance motor is widely used in the industry we need to control the switched reluctance motor without using the sensors. Here main aim is to avoid the use of position sensors in the system.


Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3517 ◽  
Author(s):  
Hui Cai ◽  
Hui Wang ◽  
Mengqiu Li ◽  
Shiqi Shen ◽  
and Yaojing Feng

The precise estimation of position is an essential concern for the control of a switched reluctance motor (SRM). Given the prominent role of position, the promising sensorless control approach for an SRM drive should be capable of providing accurate position. An inductance-based approach has been widely applied in the position estimation. However, the estimated accuracy suffers from the magnetic saturation effect, resulting in the poor performance of sensorless operation. This paper presents a reversible synchronization of commutation with the corresponding rotor position for SRM. With the consideration of magnetic saturation, the proposed approach is taken as a suitable candidate and plays an essential role in accommodating the requirement of optimal control. The relationship between a typical inductance position and magnetic circuit saturation is investigated. The instant of the intersections is sensed by comparing the instantaneous inductance of adjacent phases. Thus, the predicted position is obtained with the information of the special point and the calculated average speed. Compared with other existing methods, the proposed approach has the certain advantages, such as the ability to update the estimated speed and position six times per electrical period, which guarantees the estimated accuracy. The proposed approach is also valid even when the motor is operated at an acceleration state and heavy load operation. In addition, the requirement of the educated inductance structure is not unnecessary, less memory space is needed in the chip, and the accumulated error is eliminated. The simulation and experimental findings demonstrate the feasibility and practicality of the proposed position estimation approach with carrying out the inertial operation, load mutation, and high-speed test.


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