• Proceedings of the KIPE Conference
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• 1998.07a
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• pp.366-370
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• 1998

Indirect vector control for induction motors requires the use of observers for estimation or observation of rotor flux magnitude and position. In this paper, authors discribe the induction motor vector control and introduce a nonlinear observer, named ELO(extended Luenberger Observer), without simulation results as a preliminary work for trial application. Normally, design of nonlinear observer need coordinate transfromation and linearization through solving the partial different equation. However, ELO requires minimal solution of nonlinear partial differential equation. Simulation was performed by under the enviroment of Matlab and Simulink without the proposed observer because we are still working. Simulation was performed with conventional flux observer, a dc-ac inverter by SVPWM technique, a vector controller armed with multiple PI controllers

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.12
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• pp.1836-1842
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• 2012

Torque is proportional to the rate of change of inductance in a switched reluctance motor (SRM), and hence, phase inductance is an important parameter in determining the behavior of an SRM. Therefore, the accurate prediction of inductance with respect to rotor position makes a significant contribution to designing an SRM and its analytical approach is not straightforward due to nonlinear flux distribution. Although several different approaches using a finite element analysis (FEA) or curve-fitting tool have been employed to compute phase inductance [2-5], they are not suitable for a simple design procedure because the FEA necessitates a large amount of time in both modeling and solving with complexity for every motor design, and the curve-fitting requires the data of flux linkage from either an experimental test or an FEA simulation. In this paper, phase inductance is predicted by means of a permeance method, and the proposed approach is analytically verified in terms of the accuracy of estimated inductance compared to inductance obtained by FEA.

• Proceedings of the KIPE Conference
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• 2002.11a
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• pp.3-6
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• 2002

In a conventional speed sensorless stator flux-oriented(SFO) induction motor drive system, when the estimated speed is transformed into the sample-data model using the first-forward difference approximation, the sampled data model has a modeling error which, in turn, produces an error in the rotor speed estimation. The error included in the estimated speed is removed by the use of a low pass filter (LPF). As the result, the delay of the estimated speed occurs in transients by the use of the LPF This paper investigates the problem of a conventional speed sensorless SFO system due to the delay of estimated speed in the filed weakening region. In addition, this paper proposes a method to estimate exactly speed by using Luenberger observer, The proposed method is verified by experiment with a 5-hp induction motor drive.

• 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.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1156-1165
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• 2018

This paper presents a detailed realization of direct torque controlled induction motor drive for elevator applications. The drive is controlled according to the well-known space vector modulated direct control scheme (SVM-DTC). As the elevator drives are usually equipped with speed sensors, flux estimation is carried out using a current model where two stator currents are measured and accurate instantaneous rotor speed measurement is used to overcome the need for measuring stator voltages. Speed profiling for a comfortable elevator ride and other supervisory control activities to provide smooth operation are also explained. The drive performance is examined and controllers' parameters are fine-tuned using MATLAB/SIMULINK. The blocks used for flux and torque estimation and control in the offline simulation are compiled for real-time using dSPACE Microlabox. The performance of the drive has been verified experimentally. The results show good performance under transient and steady state conditions.

• Proceedings of the KIPE Conference
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• 2001.07a
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• pp.430-433
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• 2001

When the vector control, which does not need a speed signal from a mechanical speed sensor, it is possible to reduce the cost of the control equipment and to improve the control performance in many industrial application. This paper describes a rotor speed identification method of induction motor based on the theory of flux model reference adaptive system. The estimator execute the rotor speed identification so that the vector control of the induction motor may be achieved. The improved auxiliary variable of the two model are introduced In perform accurate rotor speed estimation. The control system is composed of the PI controller for speed control and current controller using space voltage vector PWM technique. High speed calculation and processing for vector control is carried out by TMS320C31 digital signal processor. Validity of the proposed control method is verified through simulation and experimental result.

• Proceedings of the KIEE Conference
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• 2001.07b
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• pp.1172-1175
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• 2001

Recently, vector control without a speed sensor for an inverter induction motor system has been developed. In this paper describes the vector control system estimates rotor speed based on FMRAS(Flux Model Reference Adaptive System). Because of improving the initial condition and drift problem by pure integrator is eliminated, we can be expected to rapid responsibility of the speed estimation. The stability of speed estimator is proved on the basis of hyperstability theory. Proposed control system used TMS320C31 DSP for high speed processing. The effectiveness of the proposed system is verified by simulation and experimental results. This result shows that the highly characteristic speed estimation and robust character of load regulation.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.10
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• pp.107-113
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• 2002

To monitor the torque of an induction motor using current, rotating speed has been measured and used to calculate the slip angular velocity. Additional sensor, however, can cause extra expense and trouble. In this paper, a new algorithm is proposed to monitor the torque of vector controlled induction motor without any speed measuring sensor. Only stator current is measured to estimate the magnetizing current which is used to calculate flux linkage, rotor velocity and motor torque. Graphical programming is used to implement the suggested algorithm and to monitor the torque of an induction motor in real time. To solve the fluctuation problem of estimated torque caused from instantly varying rotating speed of an induction motor, the rotating speed is reconstructed based on the measured current signals. From several experiments, the proposed method shows a good estimation of the motor torque under the normal rotational speed.

• Proceedings of the KIPE Conference
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• 2004.07a
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• pp.274-278
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• 2004

This paper presents a strategy to drive built in-type spindle induction motor which is used as CNC (Computer Numerical Control) in the industrial world. The direct vector control which is robust to the changed machine parameters in the high speed range is used in this motor control method. And electrical model of induction motor presents the basic idea based on observer structure, which is composed of voltage model and current model. But the former has the defects in low speed range, the latter has the defects of sensitivity to motor parameter. Thus Gopinath model flux estimator which is the closed loop flux observer based on two models for the rotor flut estimation is used in this paper. Moreover this paper presents to drive the spindle motor in the high speed range by using the flux weakening control.

• Journal of Power Electronics
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• v.6 no.3
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• pp.235-244
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• 2006

Recently, speed sensorless vector control for synchronous reluctance motors (SYRMs) has deserved attention because of its advantages. Although rotor angle calculation using flux estimation is a straightforward approach, the DC offset can cause an increasing pure integrator error in this estimator. In addition, this method is affected by parameter fluctuation. In this paper, to control the motor at the low speed region, a modified programmable cascaded low pass filter (MPCPLF) with sensorless online parameter identification based on a block pulse function is proposed. The use of the MPCLPF is suggested because in programmable, cascade low pass filters (PCLPF), which previously have been applied to induction motors, the drift increases vastly wl)en motor speed decreases. Parameter identification is also used because it does not depend on estimation accuracy and can solve parameter fluctuation effects. Thus, sensorless speed control in the low speed region is possible. The experimental system includes a PC-based control with real time Linux and an ALTERA Complex Programmable Logic Device (CPLD), to acquire data from sensors and to send commands to the system. The experimental results show the proposed method performs well, speed and angle estimation are correct. Also, parameter identification and sensorless vector control are achieved at low speed, as well as, as at high speed.