Switched reluctance motor has features like robust structure, low cost, and wide speed extension range over conventional induction and synchronous motors. These features make it a promising choice for many applications from electric vehicle to aerospace industry.
However, due to its silent structure, the characteristics of switched reluctance motor are highly nonlinear. The nonlinearity makes it difficult to control and results in degraded performance such as high torque ripple and acoustic noise compared with conventional induction machine or synchronous machine. New power converters and control methods have to be developed to improve its performance.
In order to reduce the current ripple and torque ripple, a novel three-level converter for switched reluctance motor is proposed. The operation modes and modulation method are presented in detail. Simulation and experimental results show that compared to conventional two-level converter, the proposed three-level converter is able to reduce current ripple, torque ripple and acoustic noise significantly without increasing cost.
A fast and accurate current controller is essential for the torque control of switched reluctance motor. An adaptive current controller for the three-level converter is developed to avoid the performance degradation caused by manufacture inconsistency. This controller has the ability to adjust its parameters according to the specific motor it drives. Fast dynamic and high accuracy could be achieved through parameter adaption.
In order to reduce the cost, and compete with the well-developed sensorless brushless DC and induction motor drive system, a new position sensorless control method for switched reluctance motor is proposed. This method is effective under both low speed operation and high speed operation. It can start with heavy load. It does not have to align the machine before start up as what is needed for many sensorless brushless DC drive systems.
The proposed converter and control methods are all verified by simulation and experimental results. / Thesis / Doctor of Philosophy (PhD)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/20281 |
| Date | January 2016 |
| Creators | Peng, Fei |
| Contributors | Emadi, Ali, Electrical and Computer Engineering |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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