• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.566-569
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• 2005

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. The paper is proposed maximum torque control of IPMSM drive using artificial intelligent(AI) controller. The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using AI controller. This paper is proposed speed control of IPMSM using learning mechanism fuzzy neural network(LM-FNN) and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled LM-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also. this paper is proposed the experimental results to verify the effectiveness of AI controller.

• Journal of Power Electronics
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• 제12권3호
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• pp.468-476
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• 2012

The interior permanent magnet synchronous motor (IPMSM) has been widely used in electric vehicle applications due to its excellent power to weigh ratio. This paper proposes the maximum torque control of an IPMSM drive using an adaptive learning (AL) fuzzy neural network (FNN) and an artificial neural network (ANN). This control method is applicable over the entire speed range while taking into consideration the limits of the inverter's rated current and voltage. This maximum torque control is an executed control through an optimal d-axis current that is calculated according to the operating conditions. This paper proposes a novel technique for the high performance speed control of an IPMSM using AL-FNN and ANN. The AL-FNN is a control algorithm that is a combination of adaptive control and a FNN. This control algorithm has a powerful numerical processing capability and a high adaptability. In addition, this paper proposes the speed control of an IPMSM using an AL-FNN, the estimation of speed using an ANN and a maximum torque control using the optimal d-axis current according to the operating conditions. The proposed control algorithm is applied to an IPMSM drive system. This paper demonstrates the validity of the proposed algorithms through result analysis based on experiments under various operating conditions.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제55권2호
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• pp.89-97
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• 2006

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. The paper is proposed maximum torque control of IPMSM drive using learning mechanism-fuzzy neural network(LM-FNN) controller and artificial neural network(ANN). The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_{d}$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using LM-FNN controller and ANN controller. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of IPMSM using LM-FNN and estimation of speed using ANN controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled LM-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper is proposed the analysis results to verify the effectiveness of the LM-FNN and ANN controller.

• 조명전기설비학회논문지
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• 제20권10호
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• pp.47-57
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• 2006

본 논문은 ALM-FNN 제어기와 ANN 제어기를 사용하여 SynRM 드라이브의 최대토크 제어를 제시한다. 이 제어기는 인버터의 정격 전류와 전압 제한을 고려하고 전 속도 영역에 적용된다. 각 제어모드를 위하여 최대토크를 위한 최적의 d-축 전류 $^i{_d}$를 결정한다. 제시된 제어 알고리즘은 ALM-FNN 제어기와 ANN 제어기로 SynRM 드라이브 시스템을 제어하는데 적용된다. 최대토크 제어에 의하여 제어된 동작 특성은 실험을 통하여 상세히 설명한다. 또한 본 눈문은 ALM-FNN 제어기와 ANN 제어기 결과분석을 통하여 타당성을 입증한다.

• 대한전기학회논문지:시스템및제어부문D
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• 제55권3호
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• pp.110-114
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• 2006

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. In this paper maximum torque control of IPMSM drive using artificial intelligent(AI) controller is proposed. The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using AI controller. This paper is proposed speed control of IPMSM using adaptive learning mechanism fuzzy neural network(ALM-FNN) and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled ALM-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper is proposed the experimental results to verify the effectiveness of AI controller.

• 조명전기설비학회논문지
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• 제19권8호
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• pp.85-93
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• 2005

본 논문에서는 고속 드라이브를 위하여 IPMSM의 약계자 영역에서 최대 토크제어를 제시한다. 최대 토크동작을 위하여 최적 d축 전류를 결정하고 이 전류를 각 제어모드에서 사용한다. 최대 토크를 발생하기 위하여 전류 조절기의 출력인 인버터의 출력전압은 DC 링크전압을 최대로 이용한다. 제어모드의 원활한 전이는 지령신호에 기초하여 자동적으로 수행한다. 본 논문에서 제시한 최대 토크제어로 IPMSM 드라이브에 적용시험을 한다. 그리고 시험결과의 응답특성을 다양하게 분석하여 본 논문의 타당성을 입증한다.

• 전력전자학회논문지
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• 제4권5호
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• pp.474-482
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• 1999

본 논문에서는 유도전동기의 전 속도 영역에서 출력토오크를 최대화 할 수 있는 새로운 약계자 제어기를 제시하였다. 전압제한과 전류제한을 모두 고려한 약계자 영역에서의 최적해를 구하였다. 제안된 알고리즘은 자속과 속도를 근거로 하여 변동하는 전압 제한 조건을 만족시키는 전류 기준값을 구하게 된다. 따라서 고정자 전압을 최대한 활용하므로 정상상태 뿐만 아니라 전동기의 자속의 크기가 변화하는 과도상태에서도 최대 출력 토오크와 빠른제어 응답성을 얻을 수 있다. 시뮬레이션 및 실험결과를 통해 제안된 약계자 기법의 효용성을 보였다.

• Journal of Electrical Engineering and Technology
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• 제8권1호
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• pp.110-117
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• 2013

Maximum Torque Per Amp (MTPA) control for induction motor drives seeks to achieve a desired torque with the minimum possible stator current. This is favorable in terms of inverter operation and nearly optimal in terms of motor efficiency. However, rotor resistance variation can cause significant performance degradation. This work demonstrates that existing MTPA controls perform sub-optimally as temperature varies. An adaptive MTPA control strategy is proposed that always achieves optimal performance without exhibiting hunting phenomenon regardless of rotor temperature. The proposed control is experimentally shown to accurately achieve the desired torque.

• Journal of Power Electronics
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• 제14권2호
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• pp.341-350
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• 2014

The torque ripple of switched reluctance motors (SRMs) is the main disadvantage that limits the industrial application of these motors. Although several methods for smooth-toque operation (STO) have been proposed, STO works well only within a certain torque and speed range because of the constraints of the supply voltage and peak current. Based on previous work that sought to expand the STO range, a scheme is developed in this study to determine the maximum smooth torque range at each speed. The relationship between the maximum smooth torque and speed is defined as the smooth torque speed characteristics (STSC), a concept similar to torque speed characteristics (TSC). STSC can be utilized to evaluate torque utilization by comparing it with TSC. Thus, the concept benefits the special design of SRMs, especially for the generation of smooth torque. Furthermore, the torque sharing function (TSF) derived from the proposed method can be applied to STO, which produces a higher smooth torque over a wider speed range in contrast to four typical TSFs. TSimulation and experimental results verify the proposed method.

• 전력전자학회논문지
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• 제8권3호
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• pp.221-229
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• 2003

IPMSM은 고효율, 고성능으로 전동기로서 전기 자동차의 적용분야에 적용되고 있다. 본 논문에서는 전기자동차의 구동을 위하여 PMSM의 약계자 영역에서 최대 토크제어를 제시한다. 최대 토크동작을 위하여 최적 d축 전류를 결정하고 이 전류를 각 제어모드에서 사용한다. 최대 토크를 발생하기 위하여 전류 조절기의 출력인 인버터의 출력 전압은 DC 링크전압을 최대로 이용한다. 제안한 IPMSM 최대 토크제어의 특성을 제시하고 타당성을 입증한다.