Simultaneous rotor and stator resistance estimation of squirrel cage induction machine with a single extended kalman filter

Abstract

Accurate knowledge of rotor and stator resistance variations in a squirrel-cage induction motor (SCIM) is crucial for the performance of sensorless control of SCIM over a wide range of speeds. This study seeks to address this issue with a single Extended Kalman Filter (EKF) based solution, which is also known to have accuracy limitations when a high number of parameters/states are estimated with a limited number of inputs. To this aim, different from the author's previous approach in operating several EKFs in an alternating manner (the so-called braided EKF), an 8^{th}-order EKF is implemented in this study to test its performance for the simultaneous estimation of rotor and stator resistances with a single algorithm. Beyond the resistances, the EKF observer also estimates the load torque, rotor and stator fluxes and speed in the wide speed range (-n_{max}