TY - JOUR
T1 - Parameter estimation method for induction machines using instantaneous voltage and current measurements
AU - Rengifo-Santana, Johnny Wladimir
AU - Benzaquen-Suñe, Joseph
AU - Aller-Castro, José Manuel
AU - Bueno-Montilla, Alexander Alfredo
AU - Restrepo-Zambrano, José Alex
PY - 2015/1/1
Y1 - 2015/1/1
N2 - This paper proposes an off-line method to determine the electrical parameters of an induction machine based on two instantaneous indicators (impedance and power). The method uses the induction machine start-up voltage and current measurements. Also, the proposed method employs a space vector dynamic model of the induction machine referred to the fixed stator reference frame. This model allows the representation of the instantaneous indicators in terms of the machine electrical parameters. An error function is defined using the indicators obtained from the measurements, versus the corresponding derived from the dynamic model of the machine. The estimated parameters are obtained by minimizing this error function by means of a constrained nonlinear optimization algorithm. The effectiveness of the proposed method was experimentally validated. The results from the model using the estimated parameters fit the experimental data sets with average error below 5%.
AB - This paper proposes an off-line method to determine the electrical parameters of an induction machine based on two instantaneous indicators (impedance and power). The method uses the induction machine start-up voltage and current measurements. Also, the proposed method employs a space vector dynamic model of the induction machine referred to the fixed stator reference frame. This model allows the representation of the instantaneous indicators in terms of the machine electrical parameters. An error function is defined using the indicators obtained from the measurements, versus the corresponding derived from the dynamic model of the machine. The estimated parameters are obtained by minimizing this error function by means of a constrained nonlinear optimization algorithm. The effectiveness of the proposed method was experimentally validated. The results from the model using the estimated parameters fit the experimental data sets with average error below 5%.
KW - Induction machines
KW - Nonlinear estimation
KW - Parameter estimation
KW - Rotating machine transient
UR - http://www.scopus.com/inward/record.url?scp=84930248986&partnerID=8YFLogxK
U2 - 10.17533/udea.redin.n75a07
DO - 10.17533/udea.redin.n75a07
M3 - Article
AN - SCOPUS:84930248986
SN - 0120-6230
VL - 1
SP - 57
EP - 66
JO - Revista Facultad de Ingenieria
JF - Revista Facultad de Ingenieria
IS - 75
ER -