A real-time parameter identification scheme for the sensorless control of induction motors using a reduced order model

An observer-based systematic parameter identification scheme for an induction motor is proposed by utilizing the Lyapunov stability criteria. Assuming that all the motor parameters except the stator resistance are not known, a parameter update law is derived based on a reduced (second) order dynamic model. The model reduction is achieved by substituting the estimated value of the rotor flux into the stator current equation. The rotor flux is calculated from the stator current and the stator flux, and the stator flux is estimated by integrating voltage terms numerically. As practical examples, two identification problems are considered. Both simulation and experiment results show that the estimated values converge to the real ones with the proposed identification algorithm. This algorithm can be applied to the real sensorless vector control of induction motors.