Estimation of speed, stator temperature and rotor temperature in cage induction motor drive using the extended Kalman filter algorithm

Application of the extended Kalman filter (EKF) algorithm to the estimation of speed, stator temperature and rotor temperature in induction motor drives is described. The estimation technique is based on a closed-loop observer that incorporates mathematical models of the electrical, mechanical and thermal processes occurring within the induction motor. Speed and temperature estimation is independent of the drive´s operating mode, though closed-loop estimation is possible only if stator currents are nonzero. The EKF algorithm used to perform the estimation process has been implemented using a TMS320C30 digital signal processor and experimental results demonstrate the effectiveness of the new estimation algorithm