• 전력전자학회논문지
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• 제16권3호
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• pp.266-273
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• 2011

본 논문에서는 매입형 영구자석 동기 전동기(IPMSM)의 확장형 역기전력(EEMF) 모델을 이용한 저감차수 병렬형 확장형 칼만 필터(EKF)를 이용한 센서리스 제어 기법을 제안한다. 제안된 센서리스 제어 기법은 간단한 수학적 구조로 매입형 영구자석 동기전동기 구동에 적합한 확장형 역기전력 모델을 이용하여 두 개의 저감 차수 형태로 표현하였다. 이러한 두 모델은 매 샘플링 시간마다 확장형 칼만 필터에 번갈아 연산된다. 행렬의 차수를 저감하여 EKF의 연산시간의 단축과 알고리즘 구현의 부담을 줄였으며 센서리스 제어의 안정적인 상태 벡터의 추정을 위해 병렬로 구동하는 두 모델에 의해 추정된 정보를 이용하였다. 제안된 기법은 실험 결과를 통하여 안정적인 위치 추정 및 속도 추정 성능을 검증 하였으며, 전 차수 EKF와의 연산 시간 비교를 통하여 우수성을 검증하였다.

• 전력전자학회논문지
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• 제11권1호
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• pp.29-37
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• 2006

본 논문에서는 LM-FNN(learning Mechanism-Fuzzy Neural Network) 제어기를 이용하여 IPMSM 드라이브의 고성능 속도를 제어한다. 고성능제어를 위하여 신경회로망과 퍼지제어를 혼합 적용한 FNN을 설계한고 더욱 성능을 개선하기 위하여 학습 메카니즘을 이용하여 FNN 제어기의 파라미터를 갱신시킨다. 그리고 ANN(Artificial Neural Network)을 이용하여 IPMSM 드라이브의 속도 추정기법을 제시한다. 추정속도의 타당성을 입증하기 위하여 시스템을 구성하여 제어특성을 분석한다. 그리고 추정된 속도를 지령속도와 비교하여 전류제어와 공간벡터 PWM을 통하여 IPMSM의 속도를 제어한다. 본 연구에서 제시한 LM-FNN과 ANN 제어기의 제어특성과 추정성능을 분석하고 그 결과를 제시한다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 제40회 하계학술대회
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• pp.869_870
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• 2009

This paper presents optimal design of tooth and yoke width for increasing torque density when designing concentrated winding Interior Permanent Magnet Synchronous Motor(IPMSM) which is used currently. In case of IPM, characteristic of motor chages according to saturation, thus design consib dering saturation should be done. This paper proposed method to decide tooth and yoke width using magnetic equivalent circuit with calculated magnetic resistance. This method provide less effort and time than FEM using optimal design when deciding tooth and yoke width. Proposed method and FEM are compared and verified.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.310-313
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• 2003

This paper is proposed new fuzzy controller for high performance of interior permanent magnet synchronous motor (IPMSM) drive New fuzzy controller take out appropriate amounts of accumulated control input according to fuzzy described situations in addition to the incremental control input calculated by conventional direct fuzzy controller. The structures of the proposed controller is motivated by the problems of direct fuzzy controller. The direct controller generally give inevitable overshoot when one tries to reduce rise time of response especially when a system of order higher than one is under consideration. The undesirable characteristics of the direct fuzzy controller are caused by integrating operation of the controller, even though the integrator itself is introduced to overcome steady state error in response. Proposed controller fuzzy clear out integrated quantities according to situation. This paper attempts to provide a thorough comparative insight into the behavior of IPMSM drive with direct and new fuzzy speed controller. The validity of the comparative results is confirmed by simulation results for IPMSM drive system.

• 조명전기설비학회논문지
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• 제26권12호
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• pp.9-20
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• 2012

This paper proposes the efficiency optimization control of interior permanent magnet synchronous motor(IPMSM) drive using series connected-fuzzy neural network PI(SC-FNPI) controller. The PI controller is generally used to control IPMSM drive in industrial field. However, the PI controller has problem which is falling control performance about parameter variation such as command speed, load torque and inertia due to fixed gain of PI controller. Therefore, to improve performance of PI controller, this paper proposes SC-FNPI controller adjusted input of PI controller by FNN controller according to operating conditions. Also, this paper proposes efficiency optimization control which is improving efficiency with minimize loss. The SC-FNPI controller proposed in this paper is compared control performance with conventional FNN and PI controller about command speed, load torque and inertia variation. And the efficiency optimization control is compared with $i_d=0$ control about loss and efficiency. The SC-FNPI controller proposed in this paper shows more excellent control performance for rising time, overshoot and steady-state error. Also efficiency optimization control is increased efficiency by reducing loss.

• 전력전자학회논문지
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• 제17권3호
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• pp.213-221
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• 2012

In a PWM inverter-fed IPMSM (Interior Permanent Magnet Synchronous Motor) drive, a dead time is inserted to prevent a breakdown of switching device caused by the short-circuit of DC link. This distorts the inverter output voltage resulting in a current distortion and torque ripple. In addition to the dead time, nonlinearity exists in switching devices of the PWM inverter, which is generally dependent on operating conditions such as the temperature, DC link voltage, and current. The voltage disturbance caused by the dead time and inverter nonlinearity directly influences on the inverter output performance, and it is known to be more severe at low speed. In this paper, a new compensation scheme for the dead time and inverter nonlinearity under the parameter variation is proposed for a PWM inverter-fed IPMSM drive. The overall system is implemented using DSP TMS320F28335 and the validity of the proposed algorithm is verified through the simulation and experiments.

• 한국정밀공학회지
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• 제31권2호
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• pp.105-112
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• 2014

This paper proposes a novel $H{\infty}$ T-S Fuzzy controller with a weighted integral action for Interior Permanent Magnet Synchronous Motor(IPMSM) which have nonlinear dynamics. The $H{\infty}$ T-S Fuzzy controller is used for the robustness of nonlinear systems and the weighted integral action is used for the tracking problem and the improvement of control performance. A T-S Fuzzy controller is designed by combining the local controllers with the overall stability, and LMI(Linear Matrix Inequality)is used to determine the gains of linear controllers. The tracking problem of IPMSM is changed into regulator problem by introducing the integral action and the weighting factor gives flexibility to a $H{\infty}$ fuzzy controller.

• Journal of Electrical Engineering and Technology
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• 제13권2호
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• pp.752-760
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• 2018

In this paper, interior permanent magnet synchronous motor (IPMSM) design for sensorless drive, considering magnetic neutral point shift according to magnetic saturation, has been proposed. Sensorless control was divided into a method based on inductance and a method based on back induced voltage. Because induced voltage is very small at zero or low speed, error in rotor initial position estimation may occur. Using the ratio of saliency addresses this problem. When using high-frequency injections at low speed, the rotor's initial position is estimated at the smallest portion of the inductance. IPMSM has the minimum inductance at the d-axis. However, if magnetic saturation leads to magnetic neutral point variation, following the load current change, there is a change in the minimum point of inductance. In this case, it can lead to failure of initial rotor position estimation. As a result, it is essential that the blocking design has an inductance minimum point shift. As such, in this study, an IPMSM design method, by blocking magnetic neutral point change, has been proposed. After determining the inductance profile based on the finite element analysis (FEA), the results of proposed method were verified.

• Journal of Electrical Engineering and Technology
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• 제13권1호
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• pp.451-459
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• 2018

This work presents an approach for modeling of electric vehicle considering the vehicle dynamics, drive train, rotational wheel and load dynamics. The system is composed of IPMSM (Interior Permanent Magnet Synchronous Motor) coupled with the wheels through a drive train. Generally, IPMSM is controlled by ordinary PID controllers. Performance of the ordinary PID controller is not satisfactory owing to the difficulties of optimal gain selections. To overcome this problem, a new type of fuzzy logic gain tuner for PID controllers of IPMSM is required. Therefore, in this paper fuzzy logic based gain tuning method for PID controller is proposed and compared with some previous control techniques for the better performance of electric vehicle with an optimal balance of acceleration, speed, travelling range, improved controller quality and response. The model was developed in MATLAB/Simulink, simulations were carried out and results were observed. The simulation results have proved that the proposed control system works well to remove the transient oscillations and assure better system response in all conditions.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 춘계학술대회 논문집 에너지변화시스템부문
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• pp.225-227
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• 2009

The conventional fixed gain PI controller is very sensitive to step change of command speed, parameter variation and load disturbances. The precise speed control of interior permanent magnet synchronous motor(IPMSM) drive becomes a complex issue due to nonlinear coupling among its winding currents and the rotor speed as well as the nonlinear electromagnetic developed torque. Therefore, there exists a need to tune the PI controller parameters on-line to ensure optimum drive performance over a wide range of operating conditions. This paper is proposed artificial intelligent-PI(AIPI) controller of IPMSM drive using adaptive learning mechanism(ALM) and fuzzy neural network(FNN). The proposed controller is developed to ensure accurate speed control of IPMSM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. The PI controller parameters are optimized by ALM-FNN at all possible operating condition in a closed loop vector control scheme. The validity of the proposed controller is verified by results at different dynamic operating conditions.