Identification of induction motor parameters from transient statorcurrent measurements
Shaw, S.R.; Leeb, S.B.
Industrial Electronics, IEEE Transactions on
Volume 46, Issue 1, Feb 1999 Page(s):139 - 149
Digital Object Identifier 10.1109/41.744405
Summary:This paper describes three methods for estimating the lumped model
parameters of an induction motor using startup transient data. A
three-phase balanced induction motor is assumed. Measurements of the
stator currents and voltages are required for the identification
procedure, but no measurements from the motor shaft are needed. The
first method presented applies simple models with limited temporal
domains of validity and obtains parameter estimates by extrapolating the
model error bias to zero. This method does not minimize any specific
error criterion and is presented as a means of finding a good initial
guess for a conventional iterative maximum-likelihood or least-squares
estimator. The second method presented minimizes equation errors in the
induction motor model in the least-square sense using a
Levenburg-Marquardt iteration. The third identification method is a
continuation of the Levenburg-Marquardt method, motivated by observed
properties of some pathological loss functions. The third method
minimizes errors in the observations in the least-squared sense and is,
therefore, a maximum-likelihood estimator under appropriate conditions
of normality. The performance of the identification schemes is
demonstrated with both simulated and measured data, and parameters
obtained using the methods are compared with parameters obtained from
standard tests
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