• 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 the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.455-464
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• 2019

The sensorless control based on the flux linkage of PM synchronous motors has excellent position estimation characteristics at low speeds. However, a limitation arises because the integrator of flux estimator is saturated by the DC offset generated during the analog to digital conversion(ADC) process of the measured current. In order to overcome this limitation, HPF with a low cutoff frequency is used. However, the estimation performance is deteriorated (Ed- the verb deteriorate already includes the meaning of 'problem') at high speed due to the low cutoff frequency, and increasing the cutoff frequency of the HPF induces further problems of phase leading and initial starting failure at low speeds. In this paper, the cutoff frequency of HPF was synchronized to the operation frequency of the motor: at low speeds the cutoff frequency was set to low in order to reduce the phase leading of the estimated flux, and at high speeds it was set to high to raise the DC offset removal performance. As a result, the operating range was increased by 200%. Furthermore, a phase compensation algorithm is proposed to reduce the phase leading of the HPF to less than 1.5 degrees over the full operating range. The proposed sensorless control algorithm was verified by experiment with a PM synchronous motor for a washing machine.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.383-391
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• 1993

In this paper, a new automatic cardiac output control algorithm without any pressure sensors for the motor-driven electromechanical total artificial heart(TAH) was developed using motor current information. In the previous studies, many transducers were utilized to obtain informations of hemodynamic states for the automatic cardiac output control. But. such automatic control with sensors has some problems. To solve these problems, I proposed a new "sensorless" automatic cardiac output control algorithm providing the adequate cardiac output to the time-varying physiological demand without right atrial collapse. In-vitro tests were performed to evaluate the performance of a new algorithm and it satisfied the basic three requirements on the pump output response through the mock circulation tests.

• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.298-303
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• 1998

In the speed sensorless control of the induction motor, the machine parameters (especially the secondary resistance R2) have a strong influence to the speed estimation. It is known that the simultaneous estimation of the speed and R2 is impossible in the slip frequency type vector control, because the secondary flux is constant. But the secondary flux is not always constant in the speed transient state. In this paper the R2 estimation in the transient state without adding any additional signal to the stator current is proposed. This algorithm uses the least mean square algorithm and the adaptive algorithm, and it is possible to estimate the R2 exactly. This algorithm is verified by the digital simulations and the experiments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.104-111
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• 2018

The sensorless control of high efficiency air compressors using a permanent magnet type synchronous motor as an oil-free air compressor is quite common. However, due to the nature of the air compressor, it is difficult to install a position sensor. In order to control the permanent magnet type synchronous motor at variable speed, the inclusion of a position sensor to grasp the position of the rotor is essential. Therefore, in order to achieve sensorless control, it is essential to use a permanent magnet type synchronous motor in the compressor. The position estimation method based on the back electromotive force, which is widely used as the sensorless control method, has a limitation in that position errors occur due either to the phase delay caused by the use of a stationary coordinate system or to the estimated back electromotive force in the transient state caused by the use of a synchronous coordinate system. Therefore, in this paper, we propose a method of estimating the position and velocity using a rotation angle tracking observer and reducing the speed ripple through a disturbance observer. An experimental apparatus was constructed using Freescale's MPU and the feasibility of the proposed algorithm was examined. It was confirmed that even if a position error occurs at a certain point in time, the position correction value converges to the actual vector position when the position error value is found.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.55 no.3
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• pp.133-140
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• 2006

This paper is proposed an efficiency optimization control algorithm for a synchronous reluctance motor(SynRM) which minimizes the copper and iron losses. Also, this paper presents a speed estimated control scheme of SynRM using artificial neural network(ANN). There exists a variety of combinations of d and q-axis current which provide a specific motor torque. The objective of the efficiency optimization controller is to seek a combination of d and q-axis current components, which provides minimum losses at a certain operating point in steady state. It is shown that the current components which directly govern the torque production have been very well regulated by the efficiency optimization control scheme. The proposed algorithm allows the electromagnetic losses in variable speed and torque drives to be reduced while keeping good torque control dynamics. The control performance of ANN is evaluated by analysis for various operating conditions. Analysis results are presented to show the validity of the proposed algorithm.

• Journal of Power Electronics
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• v.1 no.1
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• pp.1-8
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• 2001

The elimination of a pole sensor is desirable due to the low-cost requirement, the compactness, and the applied drives. This paper proposes the algorithm for the initial pole-position estimation of a surface permanent magnet linear synchronous motor (PM-LSM), which is carried out under the closed loop control without a pole sensor and is insensitive to the motor parameters. This algorithm is based on the principle that the initial pole position (IPP) is estimated by the trigonometric function of the two reference currents. The effectiveness of the proposed algorithm is confirmed by testing a surface PM-LSM with large disturbance, which result shows that IPP is well estimated within a satisfied moving-distance and a shorter estimation taken-time even if large disturbance such as cogging and friction is existed.

• 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.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.7
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• pp.437-442
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• 2005

In order to realize the speed control of an induction motor, the information of the rotor speed is needed. So the speed sensor as an encoder or a pulse generator is used to obtain it. But the use of speed sensor occur the some problems in the control system of an induction motor. To solve the problems, the appropriate speed estimation algorithm is used instead of the speed sensor. Also there is the limitation to improve the speed control performance of an induction motor using the existing speed estimation algorithm. Therefore, in this paper, intelligent speed estimator using Fuzzy-Neural systems as adaptive laws in Model Reference Adaptive System is proposed so as to improve the existing estimation algorithm and ,using the rotor speed estimated by the Proposed estimator, the speed control of an induction motor without speed sensor is performed. The computer simulation and the experiment is executed to prove the performance of the speed control system usinu the proposed speed estimator.

• The Transactions of the Korean Institute of Power Electronics
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• v.7 no.5
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• pp.427-436
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• 2002

This paper presents an implementation of high-dynamic performance of position sensorless motion control system of Reluctance Synchronous Motor(RSM) drives for an industrial servo system with direct torque control(DTC). The problems of high-dynamic performance and maximum efficiency RSM drives controlled by DTC are saturation of stator linkage flux and nonlinear inductance characteristics with various load currents. The accurate estimation of the stator flux and torque are obtained using stator flux observer of which a saturated inductance $L_d$ and $L_q$ can be compensated by adapting from measurable the modulus of the stator current and rotor position. To obtain fast torque response and maximum torque/current with varying load current, the reference command flux is ensured by imposing $I_{ds} = I_{qs}$. This control strategy is proposed to achieve fast response and optimal efficiency for RSM drive. In order to prove rightness of the suggested control algorithm, the actual experiment carried out at $\pm$20 and $\pm$1500 rpm. The developed digitally high-performance motion control system shown good response characteristic of control results and high performance features using 1.0kW RSM which has 2.57 Ld/Lq salient ratio.