Brushless motors are increasingly popular because of their high power density, torque to inertia ratio and high efficiency. However an operational characteristic is the occurrence of torque ripple at low speeds. For demanding direct drive applications like machine tools, robot arms or aerospace applications it is necessary to reduce the level of torque ripple. This thesis presents an in depth investigation into the production and nature of torque ripple in brushless machines. Different torque ripple reduction strategies are evaluated and one reduction strategy using Park's transform as a tool is identified as the promising strategy. The unified machine theory is checked to clarify the theory behind Park's transform; in particular assumptions made and general validity of the theory. This torque ripple reduction strategy based on Park's transform is extended to include the effect of armature reaction. A novel adaptive torque ripple reduction algorithm is designed. The ineffectiveness of the conventional approach is demonstrated. Further a novel torque ripple reduction strategy using direct measurements of the torque ripple is suggested, reducing implementation time and allowing higher accuracies for torque ripple reduction. Extensive measurements from the experimental system show the validity of the novel torque ripple reduction strategies. The experimental results allow derivation of a formula for all load situations. This formula makes it possible to further increase the reduction accuracy and enables improved real time implementation of the torque ripple reduction algorithm. The work presented here makes a substantial contribution towards understanding the nature of torque ripple in brushless motors and solving the associated problems. The novel reduction strategies form the basis for the development of intelligent dynamometers for motor test beds. Further the torque ripple reduction method presented here can be used to overcome manufacturing imperfections in brushless machines thus removing the cost for precise manufacturing tools. Future designs of controllers can "build" their own correction formula during set-up runs, providing a motor specific torque ripple correction.

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