The flux-weakening control (FWC) methods for interior permanent magnet synchronous motors (IPMSMs) with torque performance improvement are studied in this thesis.
A FWC strategy with constant parameters is proposed, which achieves the extended dc-link voltage utilization and improves the tracking performance. The voltage trajectory is extended to the overmodulation region to increase the dc-link voltage utilization rate and torque. Moreover, a current predictive controller is implemented to improve tracking performance.
A FWC method considering the resistive voltage drop and magnetic saturation is proposed. The proposed method achieves the voltage extension, torque improvement, and improved dynamic performance by establishing a new stator flux linkage adjustment method. The stator flux linkage reference is adjusted based on the torque reference, operating speed, and modulation index. Two voltage feedback paths are established and chosen based on the torque reference and operating speed. The stator resistance and nonlinear inductance characteristics are constructed based on the experimental test. Thus, accurate current control is achieved. Compared to feedforward-based FWC methods, the proposed method improves the output torque and power. Compared to feedback-based FWC methods, the proposed method improves the dynamic performance and avoids the voltage saturation and windup problem. Compared to the mixed FWC methods, which only have one feedback path, the proposed method improves the dynamic performance.
The influence of extended dc-link voltage utilization is analyzed. The nonlinear relationship between voltage and torque is solved mathematically. The torque, torque ripple, and current ripple trends with modulation index in voltage extension region are analyzed, and the harmonic spectra of voltage, current, and torque with or without voltage extension are compared, which provide the guidance to make the tradeoff between maximizing the torque and torque ripple alleviation. / Thesis / Master of Applied Science (MASc)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/25592 |
| Date | January 2020 |
| Creators | Li, Yihui |
| Contributors | Emadi, Ali, Electrical and Computer Engineering |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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