• 산업기술연구
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• 제30권A호
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• pp.31-35
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• 2010

In this paper, a speed estimation method at coasting operation in an induction motor speed sensorless control for railway vehicle traction systems is presented. At coasting operation, there is no information obtaining rotor speed since all switches of an inverter are turned off. The inverter frequency should be synchronized with the rotor frequency for repowering at coasting condition. The proposed method injects DC current to the induction motor during a short time, then the flux angle and rotor speed needed for control can be estimated rapidly.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 B
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• pp.1081-1083
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• 2003

In this paper, a new speed sensorless induction motor scheme which can work at any speed including the zero speed is presented. The proposed method is robust to secondary resistance variations. Simultaneous estimation of speed and secondary resistance are realized based on a feedforward type torque control scheme. The secondary flux with a low frequency sinusoidal waveform is used to help the estimation. Simulations results supported by experiments are given to show the effectiveness of this method.

• 전력전자학회논문지
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• 제26권5호
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• pp.349-356
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• 2021

Permanent magnet synchronous motors are mainly used in the traction of electric vehicle and home application products including air-conditioners and refrigerators. For sensorless control without rotor position sensors, I-F control is applied for initial starting at low speeds, and mode is changed to sensorless control when the rotor speed is sufficiently accelerated for estimating rotor position. When the mode is changed to the sensorless control from the open-loop starting, the initial integral value of the speed controller should be considered by load condition; otherwise, the transition to sensorless control may fail. The sensorless transfer algorithm of PM synchronous motor based on load condition for smooth transition is proposed. The performance of the proposed sensorless transfer algorithm was verified by experiments.

• Journal of Power Electronics
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• 제10권5호
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• pp.485-490
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• 2010

Sensorless control methods are generally used in motor control for home-appliances because of the material cost and manufactureing standard restrictions. The current model-based control algorithm is mainly used for PMSM sensorless control in the home-appliance industry. In this control method, the rotor position is estimated by using the d-axis and q-axis current errors between the real system and a motor model of the position estimator. As a result, the accuracy of the motor model parameters are critical in this control method. A mismatch of the PMSM parameters affects the speed and torque in low speed, steadystate responses. Rotor position errors are mainly caused by a mismatch of the stator resistance. In this paper, a stator resistance compensation algorithm is proposed to improve sensorless control performance. This algorithm is easy to implement and does not require a modification of the motor model or any special interruptions of the controller. The effectiveness of the proposed algorithm is verified through experimental results.

• 동력기계공학회지
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• 제18권5호
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• pp.129-136
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• 2014

This paper proposes improvement on sensorless vector control performance of a permanent magnet synchronous motor (PMSM) with sliding mode observer. An adaptive observer gain and second order cascade low-pass filter (LPF) were used to improve the estimation accuracy of the rotor position and speed. The adaptive observer gain was applied to suppress the chattering intensity and obtained by using the Lyapunov's stability criterion. The second order cascade LPF was designed for the system to escalate the filtering performance of the back-emf estimation. Furthermore, genetic algorithm was used to optimize the system PI controller's performance. Simulation results showed the effectiveness of the suggested improvement strategy. Moreover, the strategy was useful for the sensorless vector control of PMSM to operate on the low-speed area.

• 한국산학기술학회논문지
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• 제8권2호
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• pp.212-218
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• 2007

본 논문에서는 MATLAB/SIMULINK와 dSPACE DS1104를 이용하여 유도 전동기의 속도 센서리스 벡터제어를 구현하였다. 유도 전동기의 속도 센서리스 벡터제어의 운전특성을 개선하기 위하여 전압 모델 자속 추정방식과 전류 모델 자속 추정방식을 혼합한 자속 추정기 알고리즘을 도입하여 정밀도가 높은 개선된 자속 추정방식을 사용하였다. 또한 추정된 자속을 이용하여 회전자 속도를 추정하고 이를 유도전동기의 속도 제어에 사용하였다. 전체 시스템은 직접벡터제어 방식을 기반으로 일반적인 PI 제어기를 사용한 속도 제어기, 전류 제어기, 자속 제어기로 구성하였다. MATLAB/SIMULINK를 이용하여 블록다이어그램 방식으로 속도 센서리스 벡터제어 알고리즘을 구현하였고, dSPACE DS1104의 제어보드와 Real-Time-Interface(RTI)를 이용하여 실시간 제어를 수행하였다.

• 전기학회논문지P
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• 제54권1호
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• pp.1-7
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• 2005

This paper is proposed the speed and position sensorless control of surface permanent magnet synchronous motor(SPMSM) with adaptive fuzzy and observer. A adaptive fuzzy controller is applied for speed control of SPMSM drive. A adaptive state observer is used for the mechanical state estimation of the motor. The observer was developed based on nonlinear model of SPMSM, that employs a d - q rotating reference frame attached to the rotor. A adaptive observer is implemented to compute the speed and position feedback signal. The validity of the proposed sensorless scheme is confirmed by various response characteristics.

• Journal of Advanced Marine Engineering and Technology
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• 제28권4호
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• pp.641-647
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• 2004

By most sensorless speed control schemes for induction motor. the control performances in high speed range are good, but it is difficult to obtain satisfactory results in low speed region. This paper proposes a new method controlling the low and the high speed regions separately to attain the stable operation in the overall range. The current error compensation method, in which the controlled stator voltage is applied to the induction motor so that the error between stator currents of the numerical model and the actual motor can be forced to decay to zero as time proceeds. is used in the low speed region In the high speed region. the method with adaptive observer is utilized. This control strategy contains an adaptive state observer for flux estimation. The rotor speed can be calculated from the rotor flux and the motor currents. The experimental results indicate good speed and load responses from the very low speed range to the high, and also show accurate speed changing performance between the low and the high speed range.

• 전기학회논문지P
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• 제55권3호
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• pp.117-122
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• 2006

The paper is proposed artificial neural network(ANN) sensorless control of induction motor drive with fuzzy learning control-fuzzy neural network(FLC-FNN) controller. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also this paper is proposed. speed control of induction motor using FLC-FNN and estimation of speed using ANN controller. The back Propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed so that the actual state variable will coincide with the desired one. The proposed control algorithm is applied to induction motor drive system controlled FLC-FNN and ANN controller, Also, this paper is proposed the analysis results to verify the effectiveness of the FLC-FNN and ANN controller.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 하계학술대회 논문집 F
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• pp.2088-2090
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• 1997

This paper consists of the speed sensorless vector control of induction motors with the estimation of rotor resistance. In the application of variable-speed induction motor drives, if an inaccurate rotor resistance is used because the rotor resistance can change due to skin effects and temperature variables, it is difficult to achieve a collect field orientation. In this paper, to overcome these difficulties adaptive algorithm is designed for rotor resistance identification. The proposed adaptive algorithm for rotor resistance estimation in the synchronous reference frame is applied by sliding mode current controller satisfing persistent excitation(PE) condition. Adaptive flux observer is here used for the purpose of estimating rotor flux and speed in the speed sensorless scheme. Computer simulations are carried out to verify the validity of the proposed algorithm.