• The Transactions of the Korean Institute of Power Electronics
• /
• v.7 no.6
• /
• pp.531-536
• /
• 2002

This paper investigates the problem of the speed controller of conventional speed sensorless stator flux-oriented(SFO) induction motor drive, and proposes a robust speed controller to solve the conventional problem. In the proposed method, a robust speed controller for speed sensorless SFO system Is designed by taking advantage of disturbance torque observer and using feedforward.

• Proceedings of the KIEE Conference
• /
• 2006.10d
• /
• pp.163-165
• /
• 2006

This paper presents a implementation of speed sensorless vector control algorithm of induction motor using MATLAB/SIMULINK amd dSPACE DSl104 R&D board. The estimation of rotor flux linkage and rotor speed is carried out using model reference adaptive system(MRAS) method. Estimated rotor speed is used to speed controller of induction motor. Simulation results are presented to confirm speed sensorless vector control algorithm.

• Journal of Institute of Control, Robotics and Systems
• /
• v.9 no.9
• /
• pp.692-699
• /
• 2003

A novel rotor speed estimation method using Model Reference Adaptive Control(MRAC) is proposed to improve the performance of a sensorless vector controller. In the proposed mettled, the stator current is used as the model variable for estimating the speed. In conventional MRAC methods, the relation between the two model errors and the speed estmation error is unclear. Yet, in the proposed method, the stator current error is represented as a function of the first degree for the error value in the speed estimation. Therefore, the proposed method can produce a fast speed estimation and is robust to the parameters error In addition, the proposed method of offers a considerable improvement in the performance of a sensorless vector controller at a low speed. The superiority of the proposed method is verified by simulation and experiment in a low speed region and at a zero-speed.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.66 no.2
• /
• pp.339-346
• /
• 2017

This paper proposes a sensorless control method to improve the performance of an internal permanent magnet synchronous motor (IPMSM) control by using a full-order flux observer in a wide speed range. The conventional sensorless control method uses a constant gain for high performance at low-speed region. However, this method has drawbacks such as an increased angle error and current ripple in the high-speed region due to the fixed gain value. In order to overcome this problem, the gain of the full-order flux observer is changed by considering the angle error in the whole speed range. The proposed method minimizes the angle error for each region of the speed range by applying a relevant gain value, which improves the current ripple reduction and motor noise cancellation. The validity of proposed sensorless control method is verified by a simulation and an experiment.

• Journal of Advanced Marine Engineering and Technology
• /
• v.36 no.6
• /
• pp.830-836
• /
• 2012

Various control algorithms have been proposed for the speed-sensorless control for an induction motor. These control schemes are mainly based on the speed feedback with the flux and speed estimations. This paper proposes another method for the speed-sensorless control for an induction motor. The proposed scheme is based on the torque and flux compensation without speed estimations, in which the same controlled stator voltage is applied to both the induction motor and the numerical model so that the differences between torques and fluxes of the model and the induction motor may be compelled to give access to zero. The results of experiment show the effectiveness of the scheme.

• Journal of Advanced Marine Engineering and Technology
• /
• v.23 no.1
• /
• pp.96-102
• /
• 1999

Sensorless speed estimation in induction motor systems is one of the most control engineers. Based on the estimated speed the vector control has been applied to the high precision torque control however most speed estimation methods use adaptive scheme so that it takes long time to estimate the speed. Thus the adaptive estimation scheme is not effective to the induction motor which requires short sampling time. In this paper a new linearized equation of induction motor system is proposed and a sensorless speed estimation algorithm based on observation techniques is developed. First the nonlinear induction motor equation is linearized at an equilibrium point. Second a proportional integral(PI) observer is applied to estimate the speed state in the induction motor system. Finally simulation results will assure the effectiveness of the new linearized equation and the sensorless estimation algorithm by using PI observer in the nonlinear induction motor system.

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

• Proceedings of the KIEE Conference
• /
• 2001.07b
• /
• pp.983-985
• /
• 2001

Sensorless induction motor drive is much studied due to the cost and reliability of speed and position sensors. Most sensorless algorithms are based on the mathematical modeling of induction motor including electrical variables such as phase current and voltage. Therefore, the accuracy of such variables largely affects the performance of sensorless induction motor drive. However, the phase voltage does not have to be directly monitored because of switching noise, and they may be reconstructed by using the command voltage. The output voltage of SVPWM-VSI supplying the motor has a considerable error, especially in a low speed range because SVPWM-VSI has a poor resolution in a low command voltage. Such a voltage information effect in speed sensorless control of induction motor has been investigated in this paper.

• Proceedings of the KIEE Conference
• /
• 2015.07a
• /
• pp.737-739
• /
• 2015

In this paper, a novel method of sensorless control scheme is proposed to apply on a single phase hybrid SRM used in high speed operation. The proposed method utilizes beneficially permanent magnet field whose performance is motor parameter independent to estimate the rotor position. Also, the current slope is adopted to complete the sensorless control when the motor running with heavy torque at high speed condition. Through this approach, the adjustable turn on/off position can be achieved without prior knowledge of inductance profile which is always employed by many sensorless schemes. And this paper may offer an available method to do the sensorless control in hybrid SRM used for high speed running.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.22 no.3
• /
• pp.66-73
• /
• 2008

This paper presents a position sensorless control system of SRM over wide speed range. Due to the doubly salient structure of the SRM, the phase inductance varies along with the rotor position. Most of the sensorless control techniques are based on the fact that the magnetic status of the SRM is a function of the angular rotor position. The rotor position estimation of the SRM is somewhat difficult because of its highly nonlinear magnetizing characteristics. In order to estimate more accurate rotor position over wide speed range, Neural Network is used for this highly nonlinear function approximation. Magnetizing data patterns of the prototype 1-hp SRM are obtained from locked rotor test, and used for the Neural Network training data set. Through measurement of the flux-linkage and phase currents, rotor position is able to estimate from current-flux-rotor position lookup table which is constructed from trained Neural Network. Experimental results for a 1-hp SRM over 16:1 speed range are presented for the verification of the proposed sensorless control algorithm.