• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1011_1012
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• 2009

Low costed position sensor or sensorless control method is generally used in the motor control for home appliance because of the material cost and manufacture standard restriction. In conventional sensorless method, the stator resistance and back-EMF coefficient are varied by the motor speed and load torque variation. Therefore, position error occurred when the motor is operated by sensorless control method because of these variations. In this paper, the compensation method is proposed for sensorless position error using the MRAS method and compared with the other sensorless control method.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.2B no.3
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• pp.125-132
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• 2002

PMSMS (permanent magnet synchronous motors) are widely used in industrial applications and home appliances because of their high torque to inertia ratio, superior power density, and high efficiency. For high performance control, accurate informations about the rotor position is essential. Sensorless algorithms have lately been studied extensively due to the high cost of position sensors and their low reliability in harsh environments. A novel position sensorless speed control for PMSMs uses indirect flux estimation and is presented in this paper. Rotor position and angular velocity are estimated by the proposed indirect flux estimation. Linkage flux and magnetic field flux are calculated by the voltage equations and the measured phase current without any integration. Instead of linkage flux calculation with integral operation, indirect flux and differential magnetic field are used for the estimation of rotor position. A proper rejection technique fur current noise effect in the calculation of differential linkage flux is introduced. The proposed indirect flux detecting method is free from the integral rounding error and linkage flux drift problem, because differential linkage flux can be calculated without any integral operation. Furthermore, electrical parameters of the PMSM can be measured by the proposed TCM (time compression method) for soft starting and precise estimation of rotor position. The position estimator uses accurate electrical parameters that are obtained from the proposed TCM at starting strategy. In the operating region, a proper compensation method fur temperature effect can compensate fir the estimation error from the variation of electrical parameters. The proposed novel position sensorless speed control scheme is verified by the experimental results.

• Journal of Power Electronics
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• v.15 no.6
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• pp.1559-1566
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• 2015

The brushless DC motor (BLDCM) has many advantages. As a result, it is widely used in electric vehicle (EV) drive systems. To improve the reliability of the motor control system, a position sensorless control strategy based on a sliding mode observer (SMO) is proposed. The global fast terminal sliding mode observer (GFTSMO) is proposed to enhance the control performance of the SMO control system. The advantages of the linear sliding mode and the nonsingular terminal sliding mode (NTSM) are combined in the control strategy. The convergence speed of the system state is enhanced. The motor commutation point is obtained with the observation of the back EMF, and the instantaneous torque value of the motor is calculated. Therefore, the position sensorless control of the BLDCM is realized. Experimental results show that the proposed control strategy can improve the convergence speed, dynamic characteristics and robustness of the system.

• The Transactions of the Korean Institute of Power Electronics
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• v.14 no.1
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• pp.82-88
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• 2009

Low costed position sensor or sensorless control method is generally used in the motor control for home appliance because of the material cost and manufacture standard restriction. In conventional sensorless method, the stator resistance and back-EMF coefficient are varied by the motor speed and load torque variation. Therefore, position error occurred when the motor is operated by sensorless control method because of these variations. In this paper, the compensation method is proposed for sensorless position error using 2 hall sensors.

• 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.17 no.3
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• pp.238-245
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• 2012

This paper presents a sensorless speed control of a 2-phase switch reluctance motor(SRM). The proposed sensorless control scheme is based on the slide mode observer with parameter compensator to improve the estimation performance. In the stand still position, the initial rotor position is determined by pulse current responses of each phase windings and the current difference. In order to determine an accurate initial rotor position, the two initial rotor positions are estimated by the difference of the pulse currents. From the stand still to the operating region, a simple open loop control which determines the commutation sequence by the pulse current of the unexcited phase winding is used. When the motor speed is reached to the sensorless control region, the estimated rotor position and speed by the slide mode observer are used to control the SRM. The flux calculator used in the slide mode observer is designed by phase voltage and the voltage drops in the phase resistance of the winding. The accuracy of the flux calculator is dependent on the phase resistance. For the continuous update of the phase resistance, current gradient at the inductance break point is used in this paper. The error of the estimated rotor position at the current gradient position is used to update the phase resistance to improve the sensorless scheme. The proposed sensorless speed control scheme is verified with a practical compressor used in home appliances. And the results show the effectiveness of the proposed control scheme.

• 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.

• The Transactions of the Korean Institute of Power Electronics
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• v.23 no.1
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• pp.16-23
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• 2018

PM synchronous motor may be rotated to an arbitrary direction and speed by outside wind under natural condition in cases where the fan is applied outside, such as in vehicle radiators and outdoor air-conditioners. Sensorless controls that cannot detect rotor position requires additional sensorless control algorithm because a rotor is rotated by an external load. In this study, the sensorless control of a PM synchronous motor under naturally rotating condition is proposed. The natural rotation conditions are classified as forward high-speed rotation, reverse high-speed rotation, and low-speed rotation. Experiment results verify the performance of the sensorless control, including the rotor speed and position detection at natural rotation mode and switch to the closed-loop sensorless control.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.8-15
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• 2019

The PM synchronous motor drives with vector control have been applied to wide fields of industry applications due to its high efficiency. The rotor position information for vector control of a PM synchronous motor is detected from the rotor position sensors or rotor position estimators. The sensorless control based on the mathematical model of PM synchronous motor is generally used and it can be classified into back EMF -based sensorless control and magnet flux-based sensorless control. The rotor position estimating performance of the back EMF-based sensorless control is deteriorated at low speeds since the magnitude of back EMF is proportional to the motor speed. The magnitude of the magnet flux for estimating rotor position in the flux-based sensorless control is independent on the motor speed so that the estimating performance is excellent for wide speed ranges. However, the estimation performance of the model-based sensorless control may be influenced by the motor parameter variation since the rotor position estimator uses the mathematical model of the PM synchronous motor. In this paper, the rotor position estimation performance for the back EMF based- and flux-based sensorless controls is analyzed theoretically and is compared through the simulation and experiment when the motor parameters including stator resistance and inductance are varied.

• Proceedings of the KIPE Conference
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• 2000.07a
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• pp.434-438
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• 2000

In this paper the low cost sensorless control circuit for a PM synchronous motor without the mechanical rotor position sensors is presented. The sensorless control algorithm and position detection circuit for the sinusoidal current wave drive is more complex than that of the rectangular current wave drive. The proposed position sensing circuit is composed of an operational amplifier and several passive elements. The design procedures for getting the optimal parameters for the position sensing circuit are presented. The performance of the proposed algorithm is verified through the simulations and experiments.