• Proceedings of the KIPE Conference
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• 2003.11a
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• pp.113-118
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• 2003

The proposed rotor time constant estimation method can be applied to the direct vector control system of induction motor with flux observer In this paper the flux observer proposed by Gopinath model are used. This paper presents a new scheme for on-line estimation of rotor time constant using estimated rotor flux phase and current model rotor flux phase. The major advantage of this method are its dynamic correction capability, simplicity and accuracy as well as independence from change in motor parameter. simulation results are presented which demonstrate the effectiveness of the on line rotor time constant estimation.

• Journal of Power Electronics
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• v.19 no.6
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• pp.1505-1514
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• 2019

The permanent magnet synchronous motor (PMSM) is widely used in various fields and the proportional-integral (PI) controller is popular in PMSM control systems. However, the motor parameters are usually unknown, which can lead to a complicated PI controller design and poor performance. In order to design a PI controller with good performance when the motor parameters are unknown, a control algorithm based on stability margin is proposed in this paper. First of all, based on the mathematical model of the PMSM and the least squares (LS) method, motor parameters are estimated offline. Then based on the estimation values of the motor parameters, natural angular frequency and phase margin, a PI controller is designed. Performance indices including the natural angular frequency and the phase margin are used directly to design the PI controller in this paper. Scalar functions of the d-loop and the q-loop are selected. It can be seen that the designed controller parameters satisfy Lyapunov large scale asymptotic stability theory if the natural angular frequencies of the d-loop and the q-loop are large than 0. Experimental results show that the parameter estimation method has good accuracy and the designed PI controller proposed in this paper has good static and dynamic performances.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.135-135
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• 2000

In this Paper. the DSP implementation of induction motor drive is Presented on the viewpoint of the design and experiment. The speed estimation of control system for induction motor drive is designed on the base of neural network speed estimator. This neural network speed estimator is experimentally applied to the induction motor system. This system Provides the satisfactory results.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.10
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• pp.1303-1307
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• 2018

A improving sensorless compensator for the IPMSM(Interior Permanent Magnet Synchronous Motor) drive system is proposed. Generally, the motor drive system is required the robust parameter variation and disturbance. The speed estimation methods of the conventional IRP(Instantaneous Reactive Power) compensator is improved by the speed estimation techniques of the current model observer with the proposed instantaneous reactive power compensator. Performance evaluations of the novel speed error compensator and sensorless control system are carried out by the experiments.

• Proceedings of the KIPE Conference
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• 2013.07a
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• pp.114-115
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• 2013

This paper proposes an estimation method of back emf for the sensorless controlled high speed PMSM drive in turbo compressors with air bearings. The back emf of PMSM motor varies due to the temperature variation, which deteriorates the control performance of sensorless controlled PMSM drives. The proposed method is based on the current model of the PMSM motor. The simulation results show that the proposed method estimates the back emf of sensorless controlled PMSM drives with reasonable accuracy for parameter adaptation.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2004.11a
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• pp.16-16
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• 2004

• The Transactions of the Korean Institute of Power Electronics
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• v.18 no.3
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• pp.289-295
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• 2013

It is important to know exact values of Interior Permanent Magnet Synchronous Motors(IPMSM)' parameters such as stator resistance and inductance in order to have their high performance. This paper proposes a novel motor parameter(stator resistance, d&q axis inductance) estimation algorithm for IPMSM. The proposed estimation method utilizes back-EMF equations and model reference adaptive system(MRAS). The algorithm using back-EMF estimates d and q axis inductances in the constant torque region, and the stator resistance is estimated by using MRAS with the estimated inductance regardless of speed regions. The validity of the proposed algorithm is verified by simulations and experiments.

• Journal of Electrical Engineering and Technology
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• v.7 no.6
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• pp.845-851
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• 2012

Power system loads have a significant impact on a system. Although it is difficult to precisely describe loads in a mathematical model, accurately modeling them is important for a system analysis. The traditional load modeling method is based on the load components of a bus. Recently, the load modeling method based on measurements from a system has been introduced and developed by researchers. The two major components of a load modeling problem are determining the mathematical model for the target system and estimating the parameters of the determined model. We use the composite load model, which has both static and dynamic load characteristics. The ZIP model and the induction motor model are used for the static and dynamic load models, respectively. In this work, we propose the measurement-based parameter estimation method for the composite load model. The test system and related measurements are obtained using transient security assessment tool(TSAT) simulation program and PSS/E. The parameter estimation is then verified using these measurements. Cases are tested and verified using the sample system and its related measurements.

• Journal of Power Electronics
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• v.10 no.1
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• pp.58-64
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• 2010

In this paper, the dynamic performance of oscillating linear motors, which are used in household refrigerators, is improved by means of efficient parameter identification. Oscillating linear motor parameters are identified as a function of the piston position and the motor current. They are stored in a ROM table and used later for an accurate estimation of piston position. The identified motor parameters are also approximated to the $2^{nd}$-order surface functions, which are divided into 2 or 4 subsections in order to decrease identification errors. Experimental results are given to show that the proposed control scheme can provide oscillating linear motors with high dynamic performance.

• Journal of Power Electronics
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• v.6 no.2
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• pp.172-177
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• 2006

This paper presents the sliding mode observer of an induction motor for the fuel cell electric vehicles. The exact rotor flux estimation of the induction motor is important for achieving the best performance from the fuel cell electric vehicle system. However, the flux estimator of the induction motor control is highly sensitive to the voltage sensor output characteristics and system parameter variation influenced by external factors. In order to eliminate these problems, this paper investigates the electric vehicle performance due to parameter variation of the induction motor. A new method to estimate the fuel cell electric vehicle system is proposed based on the sliding mode observer.