• Journal of the Korean Society for Precision Engineering
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• v.19 no.10
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• pp.107-113
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• 2002

To monitor the torque of an induction motor using current, rotating speed has been measured and used to calculate the slip angular velocity. Additional sensor, however, can cause extra expense and trouble. In this paper, a new algorithm is proposed to monitor the torque of vector controlled induction motor without any speed measuring sensor. Only stator current is measured to estimate the magnetizing current which is used to calculate flux linkage, rotor velocity and motor torque. Graphical programming is used to implement the suggested algorithm and to monitor the torque of an induction motor in real time. To solve the fluctuation problem of estimated torque caused from instantly varying rotating speed of an induction motor, the rotating speed is reconstructed based on the measured current signals. From several experiments, the proposed method shows a good estimation of the motor torque under the normal rotational speed.

• Proceedings of the KIPE Conference
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• 2002.07a
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• pp.192-195
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• 2002

The thesis proposes the sensorless vector control method that estimates the rotor speed and rotor time constant at the same time using stator current. In the proposed method, stator current error in the stationary reference frame is proportional to estimated speed error, and stator current error in the synchronous reference frame is proportional to estimated rotor time constant error. The proposed method can simultaneously produce a fast speed estimation and rotor time constant estimation. Therefore, this new method offers an improvement in the performance of a sensorless vector controller. And, the superiority of the proposed method is verified by simulation.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.9 no.4
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• pp.62-70
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• 1995

Brushless DC Motor (BDCM) is widely used in the industry such as a variable speed motor in a compressor for room air conditioners, because the motor can be easily controlled and operated over a wide speed range. The system to drive BDCM needs encoder that senses rotor position. Gut in a certain application, the position sensor has to be avoided. In the paper, various position sensorless drive systems for BDCM are investigated and critically evaluated, so that the effective method of sensorless control can be selected. Out of these methods, the freewheeling diode current sensing has many advantages. For example, the simple starting procedure makes it possible to perform sensorless control even in low speed. So the hardware design for this method has been carried out and the system has been implemented using DSP. The experimental results verified that the freewheeling diode current sensing approach has advantages in starting procedure and low speed sensing.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.53 no.4
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• pp.195-200
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• 2004

Many kinds of speed sensorless control system of induction motor had been developed. But it is difficult to implement at the real system because of complex algorithm and equations. This paper investigates a novel speed sensorless control of induction motor using neural networks. The proposed control strategy is based on neural networks using stator current and output of neural model based on state observer. The errors between the stator current and the output of neural model are back-propagated to adjust the rotor speed, so that adaptive state variable will coincide with the desired state variable. This algorithm may overcome several shortages of conventional model, such as integrator problems, small EMF at low speed and relatively large sensitivity of stator resistance variation. Also, this paper presents a newly developed optimal equation about the momentum constant and the learning rate. The proposed algorithms are verified through simulation.

• Proceedings of the KIPE Conference
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• 2004.07b
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• pp.976-980
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• 2004

This paper presents a position sensorless control system of Switched Reluctance Motor (SRM) using neural network. The control of SRM depends on the commutation of the stator phases in synchronism with the rotor position. The position sensing requirement increases the overall cost and complexity. In this paper, the current-flux-rotor position lookup table based position sensorless operation of SRM is presented. Neural network is used to construct the current-flux-rotor position lookup table, and is trained by sufficient experimental data. Experimental results for a 1-hp SRM is presented for the verification of the proposed sensorless algorithm.

• The Transactions of the Korean Institute of Power Electronics
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• v.8 no.5
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• pp.427-434
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• 2003

This paper describes a new method of detecting rotor position in switched reluctance motor(SRM), Some strategies of position sensorless control methods for the motor include the measurement of phase current and applied pulse voltage in an unexcited phase. The principle of the estimation of a rotor position is based on the detection of inductance by pulse currents. This sensorless method is very simple to compute rotor position estimation and gives efficient control of drive system. Suggested method is verified by some experimental tests.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.55 no.2
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• pp.107-115
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• 2006

In this paper, a new speed sensorless control based on an instantaneous reactive power is proposed for the interior permanent magnet synchronous motor(IPMSM) drives. In proposed algorithm, the current observer estimates the line currents and the estimated speed can be yielded from the voltage equation because the information of speed is included in back EMF. To implement speed sensorless control, the current observer is composed by using the voltage equation of the IPMSM in the stationary reference frame fixed to the stator. The estimated speed of the rotor is composed by using the voltage equation of the IPMSM in the rotating reference frame fixed to the rotor The estimated speeds to minimize the speed error compensated by using the instantaneous reactive power. The instantaneous reactive power is calculated on the rotating reference frame fixed to the rotor. The effectiveness of the preposed algorithm is confirmed by the experiments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.7
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• pp.956-962
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• 2013

Recently, sensorless controls, which eliminate position and speed sensor in a permanent magnet synchronous motor drive, have been much studied. Most sensorless control algorithms are based on the back-EMF and speed estimations which are obtained from the voltage equations. Therefore, the sensorless control performance is largely affected by the parameter errors of a motor. This paper investigates a novel adaptive control with the parameter error compensation for the speed sensorless control of a permanent magnet synchronous motor. The proposed parameter estimation is obtained from the d-axis current error between the real and estimated currents. The proposed algorithm is verified through the simulation and experimentation.

• Journal of international Conference on Electrical Machines and Systems
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• v.1 no.4
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• pp.477-482
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• 2012

This paper describes a new rotor position sensorless control method for SRM drives based on an improved simplified flux linkage method. In the traditional simplified flux linkage method, every phases take turns conduction and current chopping control method is used. Every phases take turns conduction means turning on the incoming working phase while turning off the working phase. This conduction mode causes coupling between turn-on and turn-off angles, which goes against optimal efficiency or torque ripple minimization with sensorless speed control. In the improved simplified flux linkage method, turn-off angle is calculated by flux loop, the turn-on angle can be given arbitrarily and has no relations with the turn-off angle, and the current chopping control method is used. The speed and rotor position can be estimated then. Finally, a sensorless SRM speed control system and an experiment platform with DSP are built and validity of this method is confirmed.

• The Transactions of the Korean Institute of Power Electronics
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• v.9 no.3
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• pp.246-252
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• 2004

This paper presents a position sensorless control system of Switched Reluctance Motor (SRM) using neural network. The control of SRM depends on the commutation of the stator phases in synchronism with the rotor position. The position sensing requirement increases the overall cost and complexity. In this paper, the current-flux-rotor position lookup table based position sensorless operation of SRM is presented. Neural network is used to construct the current-flux-rotor position lookup table, and is trained by sufficient experimental data. Experimental results for a 1-hp SRM is presented for the verification of the proposed sensorless algorithm.