Designing a Sensorless Torque Estimator for Direct Torque Control of an Induction Motor

Overview

The document is a thesis authored by Athanasios Tsoutsas at the Naval Postgraduate School in September 2009, focusing on the development of a sensorless torque estimator for direct torque control of an induction motor. The research addresses the pressing issue of air pollution caused by transportation, proposing electric propulsion as a viable alternative to internal combustion engines.

The thesis emphasizes the need for accurate electromagnetic torque estimation and efficient control systems to enhance the performance of electric vehicles. It outlines the design and implementation of an electromagnetic torque estimator using the Simulink/Matlab environment, integrated with XILINX block sets. This approach allows for the simulation and analysis of the torque estimator's performance in a controlled environment.

A significant aspect of the research is the verification of the torque estimator's accuracy through the use of Field Programmable Gate Arrays (FPGA). The thesis details the methodology employed to ensure that the torque estimation is reliable and can be effectively utilized in real-world applications. By leveraging advanced hardware and software tools, the study draws realistic conclusions about the performance of the electromagnetic torque estimator, which is critical for the control of electric vehicles.

The document also includes a distribution statement indicating that it is approved for public release and has unlimited distribution, making it accessible for further research and development in the field of electric propulsion and motor control systems.

In summary, this thesis contributes to the growing body of knowledge on electric vehicle technology, particularly in the area of induction motor control. It highlights the importance of developing accurate and efficient systems to facilitate the transition from traditional combustion engines to electric propulsion, ultimately aiming to reduce environmental impact and improve air quality. The findings and methodologies presented in this research are relevant for engineers and researchers working on electric vehicle systems, motor control, and related technologies.