The Transactions of the Korean Institute of Electrical Engineers P (전기학회논문지P)

The Korean Institute of Electrical Engineers (대한전기학회)
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A Direct Torque Control System for Reluctance Synchronous Motor Using Neural Network

신경회로망을 이용한 동기 릴럭턴스 전동기의 직접토크제어 시스템

  • 김민회 (영남이공대학 전기자동화과)
  • Published : 2005.03.31
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Abstract

This paper presents an implementation of efficiency optimization of reluctance synchronous motor (RSM) using a neural network (NN) with a direct torque control (DTC). The equipment circuit considered with iron losses in RSM is analyzed theoretically, and the optimal current ratio between torque current and exiting current component are derived analytically. For the RSM driver, torque dynamic can be maintained with DTC using TMS320F2812 DSP Controller even with controlling the flux level because a torque is directly proportional to the stator current unlike induction motor. In order to drive RSM at maximum efficiency and good dynamics response, the Backpropagation Neural Network is adapted. The experimental results are presented to validate the applicability of the proposed method. The developed control system show high efficiency and good dynamic response features with 1.0 [kW] RSM having 2.57 inductance ratio of d/q.

Keywords

References

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