Abstract
This paper presents a novel position estimation scheme for interior permanent magnet synchronous machines (IPMSMs) based on merging two self-sensing techniques according to the operating speed. High frequency (HF) signal injection algorithm is deployed for zero and low- speeds, while a Machine Learning (ML) method is solicited for medium and high speeds. The scheme is intended for sensorless torque-controlled drives used in electric vehicle (EV) propulsion. Typically, the proposed sensorless strategy can be applied to safety and limphome applications.
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