Sponsor
Portland State University. Department of Electrical and Computer Engineering
First Advisor
Jonathan Bird
Date of Publication
Fall 9-27-2019
Document Type
Thesis
Degree Name
Master of Science (M.S.) in Electrical and Computer Engineering
Department
Electrical and Computer Engineering
Language
English
Subjects
Magnetic devices, Gearing, Wind turbines
DOI
10.15760/etd.7056
Physical Description
1 online resopurce (x, 101 pages)
Abstract
This thesis looks at the modeling and simulation of linear and nonlinear magnetic gear dynamics in a wind turbine drivetrain. The objective is to lay the groundwork for analysis, modeling and optimization of control structures focused on pole-slip prevention. A classical mechanical two-mass torsion spring model is used as the basis for developing the dynamic system equations and Simulink models. The wind turbine torque input to the low speed rotor is modeled as a disturbance input, the generator torque is modeled as a controlled input, and the high-speed rotor speed is the only measured output. The nonlinear dynamics are linearized; and a state space model is built that utilizes both gear rotor speeds and the load angle as states. A state space feedback compensation controller is designed using pole placement techniques; and the sensitivity of the selected poles is tested across the full range of rated load angles. A full order observer is combined with state feedback compensation and the performance is evaluated with and without load angle speed regulation and integral action. A reduced order observer is designed with load torque estimation as an additional "metastate", which is then used to calculate the load angle, providing a better estimate than what the observer directly provides. Finally, the accuracy of the reduced order observer is tested using real torque data from a wind turbine.
Rights
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Persistent Identifier
https://archives.pdx.edu/ds/psu/29932
Recommended Citation
Vournas, Danielle, "Modeling and Control of Magnetic Gear Dynamics in a Wind Turbine Drivetrain" (2019). Dissertations and Theses. Paper 5180.
https://doi.org/10.15760/etd.7056