Regression Techniques for Parameter Estimation of a Synchronous Machine from Sudden Short-Circuit Testing

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.