• Journal of Electrical Engineering and Technology
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• v.4 no.3
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• pp.360-364
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• 2009

This paper suggests the techniques in determining the values of the steady-state equivalent circuit parameters of a three-phase induction machine using genetic algorithm. The parameter estimation procedure is based on the steady-state phase current versus slip and input power versus slip characteristics. The propose estimation algorithm is of non-linear kind based on selection in genetic algorithm. The machine parameters are obtained as the solution of a minimization of objective function by genetic algorithm. Simulation shows good performance of the propose procedures.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.48 no.2
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• pp.75-82
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• 1999

A compensation method of the motor parameters using zero sequence third harmonic voltage is presented for the speed sensorless vector control of the induction motor considering saturation of the flux. Generally, the air-gap flux of the saturated induction motor contains the space harmonic components rotating with the synchronous frequency of the motor. Because the EMF of the saturated induction motor contains the zero sequence harmonic voltages at the neutral point of the motor, those harmonic voltages can be used as a saturation index. In this work, the rotor flux observer is firstly designed for the speed sensorless vector control of induction motor. And a novel measurement method of the space harmonic voltage and a compensation method of th LPF(Low Pass Filter) are proposed. For compensating the non-linear variations of the magnetizing inductance depending on the saturation level of the motor, the dominant third harmonic voltage of the motor is used as a saturation function of the air-gap flux. And the variation of the stator resistance owing to the motor temperature can also be measured with the phase angle between the impressed voltage vector and the zero sequence voltage. The validity of the proposed parameter compensation scheme in the speed sensorless vector control using rotor flux observer is verified by the result of the simulations and the experiments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.9
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• pp.1546-1551
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• 2008

This paper is concerned with the problems of accurate losses segregation in capacitor-run single phase motor. Segregation of losses in single phase induction motor is more complicated than that in three phase induction motor, because of the backward magnetic field component in the motor. Generally there are two methods for losses segregation of single phase induction motor. The one is relatively complicated method based on parameter estimation of single phase induction motor. By the way, the other one is simplified method based on IEEE Standard 114. All of the methods for the experimental determination of single phase induction motor losses are studied in this paper. Since the IEEE Standard is not possible to be applied for all type of single phase induction motors, we modified that method to apply for losses segregation of capacitor-run single phase induction motor as unifying the method based on parameter estimation.

• Journal of Electrical Engineering and Technology
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• v.4 no.2
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• pp.149-158
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• 2009

It is important to derive reliable parameter values in the measurement-based load model development of electric power systems. However parameter estimation tasks, in practice, often face the parameter identifiability issue; whether or not the model parameters can be estimated with a given input-output data set in reliable manner. This paper introduces concepts and practical definitions of the local identifiability of model parameters. A posteriori local identifiability is defined in the sense of nonlinear least squares. As numerical examples, local identifiability of third-order induction motor (IM) model and a Z-induction motor (Z-IM) model is studied. It is shown that parameter ill-conditioning can significantly affect on reliable parameter estimation task. Numerical studies show that local identifiability can be quite sensitive to input data and a given local solution. Finally, several countermeasures are proposed to overcome ill-conditioning problem in measurement-based load modeling.

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.425-436
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• 2016

In this paper, a parameter optimization based iterative learning control strategy is presented for permanent magnet synchronous motor control. This paper analyzes the mechanism of iterative learning control suppressing PMSM torque ripple and discusses the impact of controller parameters on steady-state and dynamic performance of the system. Based on the analysis, an optimization problem is constructed, and the expression of the optimal controller parameter is obtained to adjust the controller parameter online. Experimental research is carried out on a 5.2kW PMSM. The results show that the parameter optimization based iterative learning control proposed in this paper achieves lower torque ripple during steady-state operation and short regulating time of dynamic response, thus satisfying the demands for both steady state and dynamic performance of the speed regulating system.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.7 no.6
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• pp.34-41
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• 1993

This paper describes an effort to develop a microcomputer-based parameter identification system for three phase and two phase brushless DC motor. Back EMF equation is derived from back EMF waveform of three phase and two phase brushless DC motor. In this paper, a new identification algorithm for the brushless DC motor parameters by Pasek's technique is de veloped. It is found that Pasek's equation is valid for the brushless DC motor, too. The results obtained clearly shows that it is possible to implement the identification system for the determination of the brushless DC motor parameters. To minimize errors due to the ripple component in the measured armature current, dlgital averaging filter is employed. The whole identification process of signal generation, measuring, parameter determination is fully automated. The use of the pmpased method in the parameter identification system shows that the averaged current curve is in excellent agreement with the estimated current curve. Therefore, this close agreement conf i i the validity of this technique.

• Proceedings of the KIEE Conference
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• 1992.07b
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• pp.1215-1217
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• 1992

This Paper described the hish performance position control for elevator using induction motor and driver. In this paper, the suitable Motor specifications for elevator drive are briefly discussed and high accuracy position control for both kinds of control method is analysed considering the parameter variation in the primary and secondary resistances. Since the pre-identified values of the motor constants are used to determine the control inputs, the performance degradation is caused by the parameter variation such as in the motor resistance. Particularly, the value of secondary resistance is considered significant because the control gain to determine the slip frequency is heavily dependent on that. The new proposed method uses on special small input signal for the parameter indentification and is expected to have the high accuracy position.

• International Journal of Control, Automation, and Systems
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• v.3 no.1
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• pp.79-86
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• 2005

In this paper, an estimator scheme for the rotor speed and flux of an induction motor is proposed on the basis of a fourth-order electrical model. It is assumed that only the stator currents and voltages are measurable, and that the stator currents are bounded. There are a number of common terms in the motor dynamics, and this is utilized to find a simple error model involving some auxiliary variables. Using this error model, the state estimation problem is converted into a parameter estimation problem assuming that the rotor speed is constant. Some stability properties are given on the basis of Lyapunov analysis. In addition, the rotor resistance, which varies with the motor temperature, can also be estimated within the same framework. The effectiveness of the proposed scheme is demonstrated through computer simulations and experiments.

• Proceedings of the KIEE Conference
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• 2003.07b
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• pp.1111-1113
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• 2003

This paper proposes an effective self-turning algorithm based on Artificial Neural Network (ANN) for fuzzy speed control of the indirect vector controlled induction motor. Indirect vector control method divides and controls stator current by the flux and the torque producing current so that the dynamic characteristic of induction motor may be superior. However, if motor parameter changes, the flux current and the torque producing one's coupling happens and deteriorates the dynamic characteristic. The fuzzy speed controller of an induction motor has the robustness over the effect of this parameter variation than a conventional PI speed controller in some degree. This paper improves its adaptability by adding the self-tuning mechanism to the fuzzy controller. For tracking the speed command, its membership functions are adjusted using ANN adaptation mechanism. This adaptability could be embodied by moving the center positions of the membership functions. Proposed self-tuning method has wide adaptability than existent fuzzy controller or PI controller and is proved robust about parameter variation through Matlab/Simulink simulation.

• Proceedings of the KIPE Conference
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• 1998.11a
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• pp.68-72
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• 1998

The parameter through the motor designing program is used to predict motor response and design the motor drive circuits. The application programs such as "Saber" are often used for these. However, making the electrical model of motor for these simulation tool is uncomfortable and impossible for general users. Therefore, in this paper, we develop the "Spice" library generation program with the motor designing program "Motor Expert". This program will assist the user to make the motor library comfortablely and correctlyry comfortablely and correctly