An optimal efficiency control of reluctance synchronous motor using neural network with direct torque control

This paper presents an implementation of efficiency optimization of reluctance synchronous motor (RSM) using a neural network (NN) with an direct torque control (DTC). The equipment circuit in RSM, which consider with iron losses is theoretically analyzed and the optimal current ration between torque current and exiting current analytically derived. For RSM, torque dynamics can be maintained 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 NN is used. 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 ratio of d/q.