Parameter Sensitivity and Measurement Uncertainty Propagation in Torque-Estimation Algorithms for Induction Machines

Abstract

This paper studies measurement uncertainty propagation and parameter sensitivity based on a torque-estimation model for induction machines. The model is based on the equation that describes the interaction of rotor flux and rotor currents. Contrary to classical schemes for induction motor control, this is an open-loop scheme; however, the model still requires different machine parameters. Therefore, the parameter sensitivity of the model is performed. For validation, the model is implemented in the real-time environment dSPACE, and a test induction machine is subjected to different combinations of speed and torque profiles. The identified model can be used to replace mechanical torque-measurement devices or as a backup for a low-cost torque sensor.