Autonomous Self-Commissioning Method for Speed-Sensorless-Controlled Induction Machines

Abstract

Speed-sensorless control of ac machines at zero speed is so far only possible using signal injection methods. In particular, when applied to induction machines the spatial saturation leads to a dependence of the resulting control signals on the flux/load level. Usually, this dependence has to be identified on a special test stand during a commissioning procedure for each type of induction machine. In this paper, an autonomous commissioning method based on an artificial neural network approach is proposed that depends on neither a speed sensor present as a reference nor a load dynamometer coupled to the machine and guaranteeing constant speed. The training data for the neural network is obtained using only acceleration and deceleration measurements of the uncoupled machine. The reliability of the proposed autonomous commissioning method is proven by measurement results. When comparing the resulting sensorless control performance, the proposed commissioning method reaches the same level of performance as a manual identification method using a load dynamometer and a speed sensor.