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논문 기본 정보

자료유형
학술저널
저자정보
Jae-Sub Ko (순천대학교) Jung-Sik Choi (전자부품연구원) Dong-Hwa Chung (순천대학교)
저널정보
전력전자학회 JOURNAL OF POWER ELECTRONICS JOURNAL OF POWER ELECTRONICS Vol.12 No.3
발행연도
2012.5
수록면
468 - 476 (9page)

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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.

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Abstract
Ⅰ. INTRODUCTION
Ⅱ. SYSTEM CONFIGURATION AND OPERATION STATE
Ⅲ. MAXIMUM TORQUE CONTROL
Ⅳ. DESIGN OF THE AL-FNN CONTROLLER
Ⅴ. EXPERIMENTAL RESULTS
Ⅵ. CONCLUSIONS
APPENDIX
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