Induction motor states and parameters estimation using Extended Kalman Filter with reduced number of measurements

• Main Authors: Jirasak Laowanitwattana, Sermsak Uatrongjit
• Format: Conference Proceeding
• Published: 2018
• Subjects: Energy; Engineering
• Online Access: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84966470575&origin=inward; http://cmuir.cmu.ac.th/jspui/handle/6653943832/55691
• Institution: Chiang Mai University

© 2015 IEEE. Applying the Extended Kalman Filter (EKF) technique to estimate states and parameters of an induction motor usually requires information about the stator currents, voltages, and sometimes the rotor rotating speed is also utilized. In many usage conditions, the stator voltages have constant magnitude and frequency. According to this observation, in this work, the EKF based technique for estimating both states and parameters of induction motor's dynamic model which employs just stator currents is presented. To verify the proposed technique, three phase current data obtained from simulating a 380 V 50 Hz 4 poles squirrel cage induction motor are applied to this algorithm. The numerical experiment results indicate that the method can estimate the induction motor's states and parameters with satisfactory accuracy.