• Proceedings of the KIEE Conference
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• 2003.10b
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• pp.141-143
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• 2003

This paper proposes a new sensorless drive system for the trapezoidal Brushless Direct Current (BLDC) motor requiring mechanical position or speed sensor. The proposed method is using only one current sensor For this an indirect rotor position sensing method from the periodically variation DC Link current waveform. DC Link current waveform change from high to low when BLDC commutate status. This algorithm was verified by simulations using MATLAB SIMULINK and experiment.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.5
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• pp.635-643
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• 2018

This paper propose a method to identify the motor parameters and improve input voltage error which affect the low speed position error of the back-emf(back electromotive force) based sensorless algorithm and to secure the operation reliability and stability even in the case where the load fluctuation is severe and the start and low speed operation frequently occurs. In the model-based observer used in this paper, stator resistance, inductance, and input voltage are particularly influential factors on low speed performance. Stator resistance can cause resistance value fluctuation which may occur in mass production process, and fluctuation of resistance value due to heat generated during operation. The inductance is influenced by the fluctuation due to the manufacturing dispersion and at a low speed where the change of the current is severe. In order to find stator resistance and inductance which have different initial values and fluctuate during operation and have a large influence on sensorless performance at low speed, they are commonly measured through 2-point calculation method by 2-step align current injection. The effect of voltage error is minimized by offsetting the voltage error. In addition, when the command voltage is used, it is difficult to estimate the back-emf due to the relatively large distortion voltage due to the dead time and the voltage drop of the power device. In this paper, we propose a simple circuit and method to detect the voltage by measuring the PWM(Pulse Width Modulation) pulse width and compensate the voltage drop of the power device with the table, thereby minimizing the position error due to the exact estimation of the back-emf at low speed. The suitability of the proposed algorithm is verified through experiment.

• Journal of Power Electronics
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• v.17 no.1
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• pp.1-10
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• 2017

This paper presents a novel predictive digital control method for boundary conduction mode PFC converters without the need for detecting the inductor current. In the proposed method, the inductor current is predicted by analytical equations instead of being detected by a sensing-resistor. The predicted zero-crossing point of the inductor current is determined by the values of the input voltage, output voltage and predicted inductor current. Importantly, the prediction of zero-crossing point is achieved in just a single switching cycle. Therefore, the errors in predictive calculation caused by parameter variations can be compensated. The prediction of the zero-crossing point with the proposed method has been shown to have good accuracy. The proposed method also shows high stability towards variations in both the inductance and output power. Experimental results demonstrate the effectiveness of the proposed predictive digital control method for PFC converters.

• Proceedings of the KIEE Conference
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• 1999.07f
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• pp.2656-2658
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• 1999

This paper presents a control scheme for a three-phase PWM converter system without any voltage sensors. Two input currents and one load current are measured. In a general PWM converter system, the required AC input and DC output voltage values in order to control the converter are estimated using the differential equations of the converter from the measured input currents and load current values in the switch modes of the converter circuit. The PI controller is used as DC voltage controller and sinusoidal tracking controller which tracks directly AC input current is used as input current controller. The Proposed method is verified by simulations. This paper describes the estimation method and configuration of the controller, and discusses steady state and transient performances of the converter

• 한국태양에너지학회:학술대회논문집
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• 2011.04a
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• pp.299-303
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• 2011

This paper proposes a novel sensorless maximum power point tracking (11PPT) algorithm for PV systems. The method is based on dividing the operating time into several intervals in which the PV terminals are short circuited in one interval and the calculated short-current of the PV is obtained and used to determine the optimum operating point where the maximum output power can be obtained. The proposed MPPT algorithm has been introduced into a current-controlled boost converter whose duty ratio is controlled to the maintain MPP condition. The same sequence is then repeated regularly capturing the PV maximum power. The main advantage of this method is eliminating the current sensor. Meanwhile, this MPPT algorithm reduces the power oscillations around the peak power point which occurs with perturbation and observation algorithms. In addition, the total cost will decrease by removing the current sensor from the PV side. Finally, simulation results confirm the accuracy of the proposed method.

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.5
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• pp.694-699
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• 2012

This paper proposes a new sensorless speed control scheme of permanent magnet DC motor using a numerical model and hysteresis controller, which requires neither shaft encoder, speed estimator nor PI controllers. By supplying the identical instantaneous voltage to both model and motor in the direction of reducing torque difference, the rotor speed approaches to the model speed, namely setting value and the system can control motor speed precisely. As the numerical model whose electric parameters are the same as those of the actual motor is adopted, the armature rotating speed can be converged to the setting value by controlling torque on both sides to be equalized. And the hysteresis controller controls torque by restricting the torque errors within respective hysteresis bands, and motor torque are controlled by the armature voltage. The experiment results indicate good speed and load responses from the low speed range to the high, show accurate speed changing performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.5
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• pp.998-1004
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• 2016

This paper investigates a new sensorless control appling a virtual flux oriented vector control without the line voltage sensor for the power factor correction of 3 phase PWM converter. The DC output voltage is controlled by applying the kalman filter algorithm for the virtual flux estimation and the synchronous phase is obtained by using the estimated virtual flux equation based on kalman filter. This method is used to reduce the calculation time of the system and obtain a stable control that the input current including the harmonics and the noise is improved. The proposed system implement PFC algorithm in the variable region of DC output voltage. It can obtain the unity power factor, and can precisely control the DC output voltage in the load variation and in the variable voltage range. The performance of the proposed algorithm is verified through simulation and experiment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.8
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• pp.1743-1750
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• 2003

DC motor requires a rotor speed sensor for accurate speed control. The speed sensors such as resolvers and encoders are used as a speed detector, but they increase cost and size of the motor and restrict the industrial drive applications. So in these days, many papers have reported in the sensorless operation of DC motor〔3­5〕. This paper presents a new sensorless strategy using neural networks〔6­8〕. Neural network has three layers which are input layer, hidden layer and output layer. The optimal neural network structure was tracked down by trial and error, and it was found that 4­16­1 neural network structure has given suitable results for the instantaneous rotor speed. Also, learning method is very important in neural network. Supervised learning methods〔8〕 are typically used to train the neural network for learning the input/output pattern presented. The back­propagation technique adjusts the neural network weights during training. The rotor speed is gained by weights and four inputs to the neural network. The experimental results were found satisfactory in both the independency on machine parameters and the insensitivity to the load condition.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.12
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• pp.1253-1260
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• 1990

The traditional speed and pole position sensors, which are inevitable to drive the permanent magnet synchronous motors, are removed by the parameter identification using model reference adaptive systems. Also, the current detecting method is proposed on the synchronously rotating axis without the position information, and this enables the implementation of the proposed algorithm. The proposed methods have been confirmed both by digital simulation and experiments.

• Proceedings of the KIPE Conference
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• 1998.07a
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• pp.376-379
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• 1998

This paper be described the constant speed control of induction motor for high performance. Vector control system which is used the stator current, voltage of IM is modeled without the speed, flux sensor. The proposed control system be simulated using Matlab with Simulink. Results include the fast response of the constant speed and torque in proposed system. For high performance, this paper presents the robust characteristics of field oriented control system for IM.