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Regression Techniques for Parameter Estimation of a Synchronous Machine from Sudden Short-Circuit Testing
ISSN: 0148-7191, e-ISSN: 2688-3627
Published March 19, 2019 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
Event: AeroTech Americas
A sudden short-circuit (SSC) laboratory test of an electric machine is a commonly used procedure to estimate model parameters that accurately represent the dynamic response of the machine. While the graphical interpretation of the short-circuit current is often discussed in great detail, the numerical methods used to determine the solution for the machine parameter estimation is a challenging proposition. In this paper, the authors present an integral regression technique to fit the characteristic equation of the short-circuit current to a curve that is composed of exponential decays that trail off to an unknown steady-state value in the presence of noise. The proposed estimation method is applied to laboratory data from an aerospace synchronous machine.
CitationRobbins, B., Perdikakis, W., and Yost, K., "Regression Techniques for Parameter Estimation of a Synchronous Machine from Sudden Short-Circuit Testing," SAE Technical Paper 2019-01-1354, 2019, https://doi.org/10.4271/2019-01-1354.
Data Sets - Support Documents
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