• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.4
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• pp.217-225
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• 1996

This paper describes a high power resonant inverter for diagnostic X-ray generators using zero-voltage soft-switching technology. The system consists of a step-down chopper, a resonant phase-shift PWM inverter, a hihg-voltage diode, and high voltage cables a smoothing DC capacitor. The inverter makes use the leakage inductance of the hihg-voltage transformer and external capacitor as resonant components. The rectified input voltage is controlled by a step-down chopper with input voltage compensator. The output regualtion is obtained by a resonant phase-shift PWM inverter with the digital feedback controller using DSP (digital signal processor), resulting in fast rising time and wide output voltage variation. The theoretical results are correlated with results from an experimental prototype of a 7-kVp, 300mA (21kW).

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.5
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• pp.332-337
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• 2004

A number of techniques have been developed for estimation of speed or position in motor drives. The accuracy of these techniques is affected by the variation of motor parameters such as the stator resistance, stator inductance or torque constant. This paper is proposed a neural network based estimator for torque and stator resistance in IPMSM Drives. The neural weights are initially chosen randomly and a model reference algorithm adjusts those weights to give the optimum estimations. The neural network estimator is able to track the varying. parameters quite accurately at different speeds with consistent performance. The neural network parameter estimator has been applied to slot and flux linkage torque ripple minimization of the IPMSM. The validity of the proposed parameter estimator is confirmed by the operating characteristics controlled by neural networks control.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.12
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• pp.2179-2189
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• 2010

This paper deals with analytical techniques for performance evaluation of small scaled wind power generator with outer permanent magnet rotor. In part (1), using transfer relations theorem, magnetic field distribution characteristics by PM and armature reaction field are derived. Moreover, electrical parameters such as back-EMF, inductance and resistance are calculated from the obtained field characteristic equations. The proposed analytical techniques are validated by nonlinear finite element method using commercial software 'Maxwell' and performance experiments of the manufactured generator. In part (2), generating characteristics analysis such as constant speed characteristics and constant resistive load characteristics, and performance evaluation according to variation of wind speed will be accomplished using the derived electrical parameters.

• Proceedings of the KIPE Conference
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• 2009.11a
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• pp.96-98
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• 2009

This paper propose a method to detect the rotor position of IPMSM(Interior permanent magnet synchronous motor) at standstill without a position sensor. The proposed method is based on current variation caused by the magnetic saturation of stator core as rotor position. By choosing an appropriate voltage vector and applying it to phase winding, it enables the algorithm to discern between a north pole and south pole, and subsequently estimates an absolute position. This method dose not depend on the model of the motor and the motor parameter.

• Journal of Electrical Engineering and Technology
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• v.8 no.5
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• pp.1243-1250
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• 2013

A model of a permanent magnet synchronous motor (PMSM) with an inter turn short fault is proposed using a deformed flux model. The deformed flux model includes not only the fault winding flux information but also the inductance variation of the healthy winding considering the configuration of the winding distribution. With the deformed flux model and the positive sequence current assumption, the proposed model is derived in the positive and negative sequence synchronous reference frame (SRF). The finite elements method (FEM) simulation is applied to validate the proposed PMSM model with inter turn short fault.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.4
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• pp.185-191
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• 2010

This paper describes a new position sensorless control for the switched reluctance motor (SRM) by monitoring the rate of change of current with respect to the inductance variation. Two consecutive switch-on times in hysteresis current control are compared to calculate the rate of change of current and hence to estimate the rotor position and speed. The proposed sensorless control algorithm is simple to implement as it does not depend on extensive computation or additional hardware. Simulation and experimental results are presented to demonstrate the feasibility of the proposed sensorless control method.

• Proceedings of the KIPE Conference
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• 2004.07b
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• pp.972-975
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• 2004

This paper presents a simulation results of sensorless control of Switched Reluctance Motor(SRM) using neural network. The basic algorithm of this scheme is based on the flux linkage characteristic according to the phase current and the rotor position. A sufficient simulation data was used for neural network training. Through measurement of the phase flux linkage and phase currents the neural network is able to estimate the rotor position. The simulation result shows some good results, and possibility of this algorithm.

• Proceedings of the KIEE Conference
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• 2001.07b
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• pp.801-803
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• 2001

On this study the motor design method with fairly good characteristics and control capability as well as cooling capability is presented with considering the magnetic effect due to ventilation hole, which is installed to prevent the temperature rise. When the input voltage rises due to critical variation in traction power supply system, the final ventilation hole is presented by checking the inductance parameter with clarifying the relation between saturation of the motor core and the ventilation hole.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.429-433
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• 2007

A number of techniques have been developed for estimation of speed or position in motor drives. The accuracy of these techniques is affected by the variation of motor parameters such as the stator resistance, stator inductance or torque constant. This paper is proposed a neural network based estimator for torque and ststor resistance in IPMSM Drives. The neural weights are initially chosen randomly and a model reference algorithm adjusts those weights to give the optimum estimations. The neural network estimator is able to track the varying parameters quite accurately at different speeds with consistent performance. The neural network parameter estimator has been applied to slot and flux linkage torque ripple minimization of the IPMSM. The validity of the proposed parameter estimator is confirmed by the operating characteristics controlled by neural networks control.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.54 no.1
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• pp.22-26
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• 2005

This paper proposes the calculation method of magnetic coupling coefficient of the contactless energy transmission system by 3D finite element method with a variation of the secondary core positions. The primary, secondary self and leakage inductances and the capacitances of a resonant circuit are calculated by the finite element analysis results. From these values, the magnetic coupling coefficients are obtained. The secondary voltages and currents according to the secondary core positions are calculated by using the resonant circuit and compared.