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Induction Machine Parameterization From Limited Transient Data Using Convex Optimization
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DOI：10.1109/TIE.2021.3060668.png)
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摘要
En 中文
This article identifies the parameters of an induction machine using limited and nonintrusive observations of available input voltages, stator currents, and the rotor speed. Parameter extraction is formulated as a nonconvex estimation problem, which is then relaxed to a convex conic optimization problem. While the resulting relaxation could exhibit a satisfactory performance, there might be cases where the solution of convex relaxation fails to satisfy the dynamic equations of the machine. This is remedied through a local search approach initiated using the solution obtained from the relaxed problem. The proposed method is experimentally verified on a squirrel-cage induction machine with missing measured data. Using the measured signals as the benchmark, time-domain transients produced by the parameters estimated using the proposed method show almost 20% better match compared to time-domain transients produced by the parameters obtained via conventional testing.
Keyword:
Rotors
Stators
Transient analysis
Mathematical model
Induction machines
Current measurement
Torque
Conic relaxation
convex optimization
induction machine
parameter estimation
system identification
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期刊
IF:
7.2
论文数:
1.8W
被引数:
9.8W
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