Phd in ELECTRICAL, MATERIALS, RAW MATERIALS AND NANOTECHNOLOGY
ENGINEERING

Thesis title: Fundamental Limitations in Model-Based Position Estimation of Interior Permanent Magnet Synchronous Motor Drives

Many drive manufacturers aim to adopt sensorless control methods in modern drive systems, and the main impetus behind that is to enhance reliability and reduce costs. However, these methods exhibit inherent limitations on their performance, and parameters uncertainty leads to inaccurate rotor position estimation, compared to sensed-based drives. This research aims to develop a general approach, that can help the designers to predict and analyze position estimation errors and evaluate the dynamic performances of electro-motive-force-based observers, in order to maintain a desired performance. Complex vector modelling is used to identify the estimated position errors and dynamic properties of these observers. A unified analytical framework is presented, that allows to derive, for the first time, an exact explicit expression for the steady-state position estimation errors in which they are extensively investigated for stator resistance mismatch, inductances mismatch, voltage distortion, and current measurement errors. Sensorless control algorithms are also implemented and evaluated, as a case study, in safety-relevant steer-by-wire applications, in order to enable fail-operational performance.