• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.1
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• pp.100-110
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• 2006

This paper presents the demagnetization and iron loss analysis of the single phase Flux Reversal Machine. It has a magnetic configuration similar to the switched reluctance machine but with multipole permanent magnets of alternate polarity on each stator salient pole embraced by concentrated coils. But it can be demagnetized by sudden over current and core losses increase because switching frequency is getting faster. This paper show demagnetization of permanent magnet and iron loss characteristic, and proposed a solution.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.12
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• pp.691-699
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• 2004

SRM(Switched Reluctance Motor) drives require the accurate position information of the rotor. These informations are generally provided by a tacho generator or digital shaft-position encoder These speed sensors lower the system reliability and require special attention to noise. This paper describes a new approach to estimating SRM speed from measured terminal voltages and currents for speed sensorless control. The described method is based on the sliding mode observer. The rotor speed and position observers are estimated by the adaptation law using the real and estimated currents. However, the conventional adaptive sliding mode observer based on the variable structure control theory has some disadvantages that the estimated values including the high-frequency chattering and the steady state error generated due to the infinite feedback gain chosen and the discontinuous control input. To reduce the chattering and steady state error, an integrator is also inserted in the sliding mode observer strategy. The described adaptive sliding mode observer decreases the vibration to the switching hyper-plane of the sliding mode by adding integrator. The described methodology incorporates the Lyapunov algorithm to drive the rotor speed and the stator resistance such that it can overcome the problem of sensitivity in the face of SRM parameter variation. Also, without any mechanical information. The rotor speed of SRM is obtained form adaptive scheme. The described method is verified through the simulation and experiment.

• Proceedings of the KIPE Conference
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• 2001.07a
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• pp.243-246
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• 2001

The control of the SRM(Switched Reluctance Motor) is usually based on the non-linear inductance profiles with positions. So determination of optimal switching angle is very different. This paper proposed that the determination method of turn-on/off angle in the SRM drives is to maintain the high torque, which is realized by using self-tuning control method. During the sampling time, a number of pulses from the encoder are checked by using micro-controller. And compared with pre-checked a number of pulses. After calculating difference between two data, turn-on/off angle moves forward or backward direction by using self-tuning method. The optimal turn-on/off angle is determined by iterating such a process and the maximum torque is maintained. Experimental results are provided to demonstrate the validity of the self-tuning controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.6
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• pp.516-523
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• 2001

This paper introduces a indirect rotor position and speed estimation algorithm for the SRM(switched reluctance motor) sensorless control based on the sliding mode observer and evolutionary programming The information of position and speed is generally provided by encoder or resolve. However, the position sensor not only adds complexity, cost and size to the whole drive system, but also causes limitation for industrial applications. In this paper, in order to eliminate the position sensor, indirect position sensing, indirect position sensing method using sliding mode observer is used for SRM drives. But if sliding mode observer parameters are selected to be large, the corresponding rapid changes of estimated position and velocity result in chattering phenomenon. Therefore in order to reduce the chattering, this observer parameters are optimized by evolutionary programming. And PID controller is also optimized to track precisely for the SRM using evolutionary programming.