• Journal of Power Electronics
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• 제16권5호
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• pp.1735-1742
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• 2016

This paper proposes an interleaved five-level boost converter based on a switched-capacitor network. The operating principle of the converter under the CCM mode is analyzed. A high voltage gain, low component stress, small input current ripple, and self-balancing function for the capacitor voltages in the switched-capacitor networks are achieved. In addition, a three-loop control strategy including an outer voltage loop, an inner current loop and a voltage-balance loop has been researched to achieve good performances and voltage-balance effect. An experimental study has been done to verify the correctness and feasibility of the proposed converter and control strategy.

• Journal of Power Electronics
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• 제16권3호
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• pp.925-935
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• 2016

This paper proposes a new interleaved double-input three-level Boost (DITLB) converter, which is composed of two boost converters indirectly in series. Thus, a high voltage gain, together with a low component stress and a small input current ripple due to the interleaved control scheme, is achieved. The operating principle of the DITLB converter under the individual supplying power (ISP) and simultaneous supplying power (SSP) mode is analyzed. In addition, closed-loop control strategies composed of a voltage-current loop and a voltage-balance loop, have been researched to make the converter operate steadily and to alleviate the neutral-point imbalance issue. Experimental results verify correctness and feasibility of the proposed topology and control strategies.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2001년도 전력전자학술대회 논문집
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• pp.348-351
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• 2001

In this paper, voltage-fed high frequency resonant inverter of instantaneous current phaser control method used to DC voltage source separated is proposed. In the output control method, a novel circuit type of phase shift driving signal method with CVCF illustrated, also the operation principle of the proposed circuit is described in detail and its characteristics are presented as to normalized parameters. According to the each mode, in order to the circuit analysis and characteristic evaluation of the state equation are derives and present used to normalized parameter. In the future, this proposed inverter show that it can be practically used as power source system for the lighting equipment of discharge lamp, DC-DC converter etc.

• 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.

• 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.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2006년도 춘계학술대회 논문집
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• pp.309-314
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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. This paper proposes maximum torque control of IPMSM drive using adaptive learning fuzzy neural network and artificial neural network. This control method is applicable over the entire speed range which considered the limits of the inverter's current md 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 adaptive teaming fuzzy neural network and artificial neural network. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper proposes speed control of IPMSM using adaptive teaming fuzzy neural network and estimation of speed using artificial neural network. 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 adaptive teaming fuzzy neural network and artificial neural network, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper proposes the analysis results to verify the effectiveness of the adaptive teaming fuzzy neural network and artificial neural network.

• 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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1992년도 하계학술대회 논문집 B
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• pp.1142-1146
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• 1992

This paper deals with the operation analysis of the half-bridge parallel-resonant converter with P.W.M. control. The converter operates at fixed frequency, in the continuous and discontinuous current mode. A simplified theorectical steady-state analysis is developed and the converter characteristics are presented.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2002년도 추계학술대회 논문집
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• pp.45-48
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• 2002

Switched Reluctance Generator attracts much attention because of high efficiency, simple controllability with traction drive. But the theories that have been adopted as SRG control methods are complicated up to the present. This paper proposes reference current limitation strategy for stable generation and switching angle control in motoring mode. The proposed method is verified by simulation and experiments.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2012년도 전력전자학술대회 논문집
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• pp.423-424
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• 2012

본 논문에서는 피크 전류 모드 제어를 적용한 플라이백 컨버터의 정확한 Control-to-Output Transfer Function을 제시한다. 기존 저주파 극점만으로 간략화 된 모델은 실제 디스크리트 모델(Discrete Model)과 소신호 해석에서 많은 차이를 보인다. 본 논문에서는 정확한 저주파 극점을 유도하고, PSIM을 통한 모의실험을 통해 제안된 모델에 대한 정확성을 검증한다.