A Novel Open-Loop Speed Estimation Technique for Low-Cost IM Drives

In the last decades, several schemes have been proposed for speed-sensorless control of Induction Motor (IM) drives. Promising approaches are closed-loop observers, as Model Reference Adaptive Systems (MRAS) and Kalman filters. Recently, open-loop estimators have aroused lively interest because of their simplicity and low-cost profile. As known, open-loop algorithms use only motor equations to derive the speed estimation, whose accuracy turns out to be strictly related to the motor model and its parameters. Also the digital implementation of differentiator/integrator blocks plays a crucial role, and sometimes it reduces the applicability of open loop estimator to a limited speed range. This paper presents a novel open-loop speed estimate, with enhanced performances in terms of both speed range and robustness against parameters uncertainty. The task is accomplished with a hybrid mathematical model, which maintains a low-cost profile suitable for the industrial scenario. Extensive experimental results conclude the paper.