An Online Adaptive Stator Winding Temperature Estimator Based on a Hybrid Thermal Model for Induction Machines

Conventional thermal models with a single thermal capacitor and a single thermal resistor are incapable of giving an accurate stator winding temperature estimate tailored to the specific motor´s cooling capability. A hybrid thermal model is presented in this paper to account for the disparities in thermal operating conditions for different motors of the same rating, and of the same totally enclosed fan-cooled design. Through theoretical analysis as well as simulation, the change in the motor´s thermal behavior under impaired cooling conditions, is found to be closely related to the change in this model´s thermal resistance, R ₁. An online parameter tuning algorithm is proposed in this paper. By updating R₁ based on the rotor temperature estimated from the rotor resistance, the tuning algorithm adapts the hybrid thermal model to the changes in the motor´s thermal operating conditions. Once the hybrid thermal model is properly tuned, an adaptive stator winding temperature estimator is established. It is capable of tracking the stator winding temperature for a motor with specific cooling capability to insure complete overload protection. Experimental results validate this temperature estimator based on the hybrid thermal model and the online parameter tuning algorithm