• 전자공학회논문지B
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• 제33B권4호
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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).

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제53권5호
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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.

• 전기학회논문지
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• 제59권12호
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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.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2009년도 정기총회 및 추계학술대회 논문집
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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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• 제8권5호
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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.

• 조명전기설비학회논문지
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• 제24권4호
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• pp.185-191
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• 2010

본 논문에서는 인덕턱스의 변화에 따른 전류 변화율을 모니터링 하여 회전자의 속도 및 위치를 추정하는 센서리스 구동방법을 제안한다. 전류의 변화율은 히스테리시스 전류제어 방법을 이용하여 인접한 두 스위치 온 타임을 비교함으로써 간단히 측정할 수 있다. 제안된 방법은 복잡한 계산이나 별도의 하드웨어를 필요치 않으므로 구현이 용이하다. 시뮬레이션과 실험 결과는 제안한 방법의 실효성을 보여준다.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2004년도 전력전자학술대회 논문집(2)
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 B
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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.

• 제어로봇시스템학회논문지
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• 제13권5호
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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.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제54권1호
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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.