• The Transactions of the Korean Institute of Electrical Engineers P
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• v.65 no.1
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• pp.1-6
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• 2016

Recently, proportion of the induction motor load is gradually increased. When a contingency in the power systems, it has been discovered phenomenon that the voltage is delayed recover caused mechanical characteristics of the induction motor load. It can be a serious impact on the voltage stability of the power system considering induction motor load. The scheme to mitigate this phenomenon tripping off the motors to prevent voltage drop and delayed voltage recovery on the load demand side. Fault induced delayed voltage recovery phenomenon is caused by stalling of small induction motor load in transmission level contingencies. In this paper, fault induced delayed voltage recovery phenomenon mitigation method implementation under voltage load shedding on the korean power system considering induction motor load.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.8
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• pp.82-87
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• 2011

Induction motor is most widely used as the driving power in the industrial site. Induction motor current is composed of two parts, magnetizing current and load current. Load current uses energy what is doing the work. Load current varies with load variance but magnetizing current is constant, regardless of load variation. Magnetizing current needs for establishing the rotating magnetic field of induction motor and lags behind the voltage. Generally capacitor is used for power-factor compensation of inductive load. Self-excitation occurs when the capacitive reactive current from the capacitor is greater than the magnetizing current of the induction motor. When this occurs, excessive voltages can result on the terminals of the motor. This excessive voltage can cause insulation degradation and ultimately result in motor insulation failure. In this paper, we analyzed that how the magnetizing current and condenser current is operating at the allowable limit by the load variation. Condenser current is below allowable limit of magnetizing current but magnetizing current is above allowable limit at the lower load operation condition.

• Journal of Advanced Marine Engineering and Technology
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• v.27 no.6
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• pp.776-782
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• 2003

This paper describes a newly developed double squirrel cage induction motor in which the rotor is located outside the stator. The outside rotor type brushless dc motor has been used for VTR's head drum and PC's cooling fan, but this kind of induction motor has not been developed yet. The parameters of outside rotor type induction motor were measured from the locked rotor test and no load test. It is possible to determine the parameters which are presented in the steady-state equivalent-circuit of the outside rotor type induction motor. Load test of induction motor was carried out using a dynamometer. For the characteristics of torque, efficiency, power factor and output. the developed double squirrel cage induction motor is compared with the ordinary induction motor It is believed that the results of this paper can be used for the development of the outside rotor type induction motor.

• Journal of Electrical Engineering and Technology
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• v.9 no.1
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• pp.121-126
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• 2014

The accurate determination of induction motor efficiency depends on the estimation of the five losses of stator and rotor copper loss, iron loss, mechanical loss and stray load loss. As the mechanical and stray load losses are not calculated by electro-magnetic analysis, the values of these two losses are very important in induction motor design. In this paper, the values of mechanical loss and stray load loss are proposed through investigating testing data from commercial products of three phase induction motors under 37kW. If the values of this paper are applied to motor design, the accuracy of design and analysis can be improved. The losses of motors are obtained by using load and no-load test results following IEC 60034-2-1 standard.

• Journal of Electrical Engineering and Technology
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• v.1 no.2
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• pp.161-169
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• 2006

Load representation has a significant impact on power system analysis and control results. In this paper, composite load models are developed based on on-line measurement data from a practical power system. Three types of static-dynamic load models are derived: general ZIP-induction motor model, Exponential-induction motor model and Z-induction motor model. For the dynamic induction motor model, two different third-order induction motor models are studied. The performances in modeling real and reactive power behaviors by composite load models are compared with other dynamic load models in terms of relative mismatch error. In addition, numerical consideration of ill-conditioned parameters is addressed based on trajectory sensitivity. Numerical studies indicate that the developed composite load models can accurately capture the dynamic behaviors of loads during disturbance.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.52 no.6
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• pp.286-290
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• 2003

The high temperature superconducting bulk can be used as the bearing of induction motors. This paper presents the fabrication and test results of an induction motor with superconducting bearings using HTS bulks. The bearing had eight hexahedron type YBCO bulks. Height, width and thickness of the HTS bulk were 30mm, 30mm and 10mm, respectively. Single phase induction motor was used to drive the shaft made of aluminum and the rotor of a conventional induction motor. To estimate the performance of the HTS bulk magnetic bearing, no load test, load test and Impact test were carried out. Load tests were performed by using air resistance caused by the shaft-mounted thin cylinder with buckets. Impact tests by axial direction and vertical direction impact showed that the vibration of the shaft gradually decayed. The induction motor with HTS bulk magnetic bearing rotated silently and smoothly throughout the tests. According to the test results, conventional bearings can be replaced with superconducting magnetic bearings made of HTS bulks.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.852-856
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• 2004

An induction motor is one of the most popular electrical apparatuses owing to its simple structure and robust construction. Parameter identification of the induction motor has long been researched either for a vector control technique or fault detection. Since vector control is a well-established technique for induction motor control, this paper concentrates on successive identification of physical parameters with on-load data for the purpose of condition monitoring and/or fault detection. For extracting six physical parameters from the on-load data in the framework of the induction motor state equation, unmeasured initial state values and profiles of load torque have to be estimated as well. However, the analytic optimization methods in general fail to estimate these auxiliary but significant parameters owing to the difficulty of obtaining their gradient information. In this paper, the univariate dynamic encoding algorithm for searches (uDEAS) newly developed is applied to the identification of whole unknown parameters in the mathematical equations of an induction motor with normal operating data. Profiles of identified parameters appear to be reasonable and therefore the proposed approach is available for fault diagnosis of induction motors by monitoring physical parameters.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.7
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• pp.38-46
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• 2015

This paper propose a variable parameter estimations for variable over current load of five-phase squirrel-cage induction motor(IM) to servo control system. In order to high performance control of AC motor using a field oriented control(FOC) and direct torque control(DTC) algorithm, there are required precise motor parameters for slip calculation, flux observer, controller gain, torque command of current components, rotor position, speed estimation, and so on. We are suggest a analyzed estimation results of the motor parameters that developing five-phase squirrel-cage IM have a stator of concentrated winding for experimental within variable over current load at rated input frequency. There are results of stator winding measurement, no-load test, locked-rotor test, variable over current load test, and estimated parameters of equivalent circuits using manufactured experimental apparatus by IEEE Standard Test Procedure for Polyphase Induction Motors and Generators 112-2004.

• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.2
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• pp.99-106
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• 1998

This paper proposed a speed control system for induction motors robust to variations in torque and parameters by feedforward compensating the current portion of load torque, adding a load torque observer to the conventional PI controller in the indirect vector controlled induction motor system. Computer simulations and exeperimental works using the proposed control confirm that the transient response for the variation of the reference speed and load torque becomes improved, compared with the conventional PI controled method.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.3B no.2
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• pp.97-102
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• 2003

In this paper, a recurrent artificial neural network (RNN) based self-tuning speed controller is proposed for the high-performance drives of induction motors. The RNN provides a nonlinear modeling of a motor drive system and could provide the controller with information regarding the load variation system noise, and parameter variation of the induction motor through the on-line estimated weights of the corresponding RNN. Thus, the proposed self-tuning controller can change the gains of the controller according to system conditions. The gain is composed with the weights of the RNN. For the on-line estimation of the RNN weights, an extended Kalman filter (EKF) algorithm is used. A self-tuning controller is designed that is adequate for the speed control of the induction motor The availability of the proposed controller is verified through MATLAB simulations and is compared with the conventional PI controller.