Masters Theses

Orcid ID

Date of Award


Degree Type


Degree Name

Master of Science


Electrical Engineering

Major Professor

Hua Bai

Committee Members

Hua Bai, Leon M. Tolbert, Han Cui


As motor drive inverters continue to employ Silicon Carbide (SiC) and Gallium Nitride (GaN) devices for power density improvements, sensorless motor control strategies can be developed with field-programmable gate arrays (FPGA) to take advantage of high inverter switching frequencies. Through the FPGA’s parallel processing capabilities, a high control bandwidth sensorless control algorithm can be employed. Sensorless motor control offers cost reductions through the elimination of mechanical position sensors or more reliable electric drive systems by providing additional position and speed information of the electric motor. Back electromotive force (EMF) estimation or model-based methods used for motor control provide precise sensorless control at high speeds; however, they are unreliable at low speeds. High frequency injection (HFI) sensorless control demonstrates an improvement at low speeds through magnetic saliency tracking. In this work, a sinusoidal and square-wave high frequency injection sensorless control method is utilized to examine the impact an interior permanent magnet synchronous machine’s (IPMSM) fundamental frequency, injection frequency, and switching frequency have on the audible noise spectrum and electrical angle estimation. The audible noise and electrical angle estimation are evaluated at different injection voltages, injection frequencies, switching frequencies, and rotor speeds. Furthermore, a proposed strategy for selecting the proper injection frequency, injection voltage, and switching frequency is given to minimize the electrical angle estimation error.

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