• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.690_691
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• 2009

본 연구는 1kw급 매입형 영구자석 동기전동기(IPMSM)의 회전자의 최적 형상 설계를 위하여 여러 가지 타입의 형상을 실험 및 시뮬레이션을 통해 공극자속밀도, 쇄교자속, 역기전력, 코깅토크, 정격점에서의 최대토크, 최대토크 전류 위상각의 특성을 비교하여 구동성능을 검토하였다. 본 연구를 통하여 비교한 모델은 1kw급 매입형 영구자석 동기전동기의 기초 특성 데이터로 유용하게 이용될 수 있을 것으로 판단된다.

• Journal of Electrical Engineering and Technology
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• v.8 no.6
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• pp.1409-1414
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• 2013

A new calculation method for iron loss coefficients is proposed by using the Steinmetz equation from Epstein data. The hysteresis loss must have linear characteristic according to the frequency. However, the existing iron loss coefficients are defined by formula of frequency. In this case, the hysteresis loss has non-linear characteristics by frequency. So, in this paper, the iron loss coefficients were defined by a function of the magnetic flux density, and the iron loss calculation is applied for Interior Permanent Magnet Synchronous Motor(IPMSM) of 600(W) and 200(W). The iron loss calculation results and the experimental results are compared according to the various materials.

• Journal of Electrical Engineering and Technology
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• v.8 no.6
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• pp.1345-1351
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• 2013

Variable iron loss as function of current phase angle of Interior Permanent Magnet Synchronous Motor(IPMSM) was calculated through Curve Fitting Method(CFM). Also, a magnetic flux density distribution of iron core according to current phase angle was analyzed, and an iron loss calculation was performed including harmonic distortion. The experiment was performed by production of non-magnetizing model for the separation of mechanical loss, and the iron loss was calculated by the measurement of input using power analyzer and output power using dynamometer. Some error was generated between experimental results and calculation value, but an iron loss diminution according to current phase angle followed a same pattern. So, errors were generated by measurement, vibration, noise, harmonic distortion loss, etc.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.958-959
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• 2008

This paper is proposed a high performance speed control of the Interior Permanent Magnet Synchronous Motor through the Neural Network SV-PWM. SV-PWM is controlled using Neural Network control. SV-PWM can be maximum used maximum dc link voltage and is excellent control method due to characteristic to reducing harmonic more than others. Neural Network control has a advantage which can be robustly controlled. Simulation results are presented to show the validity of the proposed algorithm.

• Journal of Electrical Engineering and Technology
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• v.8 no.1
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• pp.118-123
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• 2013

This paper presents performance comparison between concentrated winding and distributed winding of IPMSM (Interior Permanent Magnet Synchronous Motors) which is recently used for light-weight railway applications. Motors are designed on various schemes and analyzed by using FEM (Finite Element Method) instead of EMCNM (Equivalent Magnetic Circuit Network Method) in order to take into account saturation and non-linear magnetic property. The overall performance such as torque, torque ripple, losses, demagnetization, efficiency, power density and so on are investigated in detail at the rated and maximum operating speed. The results of the analysis found that both concentrated and distributed winding IPMSMs are promising candidates for high power railway traction motor.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.934-935
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• 2015

This paper presents the sensorless control method that employs the adaptive back-EMF(Electromotive Force) and current model observer of interior permanent magnet synchronous motor(IPMSM). The estimated back EMF considering a saliency is obtained by using the adaptive control method. The estimated EMF is inputted to the current model observer which is connected in series with adaptive back EMF estimator and is used to estimate the position and speed of the rotor. In order to improve the shortcomings of conventional method using the current error components multiplied in the compensation constant, the modified instantaneous reactive power compensator is applied. The validity of the control system presented is verified by the simulation.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2008.10a
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• pp.311-314
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• 2008

This paper is proposed a high performance speed con01 of the Interior Permanent Magnet Synchronous Motor through the Fuzzy-Neuro SV-PWM, SV-PWM is controlled using Fuzzy-Neuro control. SV-PWM can be maximum used maximum dc link voltage and is excellent control method due to characteristic to reducing harmonic more than others. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability. Simulation results are presented to show the validity of the proposed algorithm.

• Proceedings of the KIPE Conference
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• 2008.10a
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• pp.175-177
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• 2008

This paper is proposed a high performance speed control of the Interior Permanent Magnet Synchronous Motor through the HAI based SV-PWM. SV-PWM is controlled using HAI control. SV-PWM can be maximum used maximum dc link voltage and is excellent control method due to characteristic to reducing harmonic more than others. The hybrid combination of fuzzy control and adaptive control will produce a powerful representation flexibility and numerical processing capability. Simulation results are presented to show the validity of the proposed algorithm.

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1108-1110
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• 2005

This paper presents a method for more efficient application of response surface methodology, one of the optimization methods, in optimal design of electrical devices. The proposed method is applied for improving torque performance of a prototype interior permanent magnet synchronous motor(IPMSM). In the end, the performance between the prototype and the optimized IPMSM is compared to verify usefulness of the method based on finite element analysis.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.59 no.3
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• pp.279-287
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• 2010

Interior permanent magnet synchronous motor(IPMSM) adjustable speed drives offer significant advantages over induction motor drives in a wide variety of industrial applications such as high power density, high efficiency, improved dynamic performance and reliability. This paper proposes efficiency optimization control of IPMSM drive using adaptive fuzzy learning controller(AFLC). In order to optimize the efficiency the loss minimization algorithm is developed based on motor model and operating condition. The d-axis armature current is utilized to minimize the losses of the IPMSM in a closed loop vector control environment. The design of the current based on adaptive fuzzy control using model reference and the estimation of the speed based on neural network using ANN controller. The controllable electrical loss which consists of the copper loss and the iron loss can be minimized by the optimal control of the armature current. The minimization of loss is possible to realize efficiency optimization control for the proposed IPMSM. The optimal current can be decided according to the operating speed and the load conditions. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using AFLC. Also, this paper proposes speed control of IPMSM using AFLC1, current control of AFLC2 and AFLC3, and estimation of speed using ANN controller. The proposed control algorithm is applied to IPMSM drive system controlled AFLC, the operating characteristics controlled by efficiency optimization control are examined in detail.