On-Line Parameter Identification of a Squirrel Cage Induction Motor

• Published in: Journal of physics. Conference series Vol. 1302; no. 2; pp. 22054 - 22060
• Main Authors: Li, Shanshan, Zhu, Ninghui, Wei, Biao, Fu, Yunji
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.08.2019
• Subjects: Coordinate transformations; Fault diagnosis; Induction motors; Least squares method; Linear equations; Low speed; Nonlinear equations; Parameter estimation; Parameter identification; Physics; Squirrel cage motors; Stators
• ISSN: 1742-6588; 1742-6596
• DOI: 10.1088/1742-6596/1302/2/022054

Based on the principle of coordinate transformation, a mathematical model of induction motors in the three-phase stationary coordinate system was transformed to that in the synchronous rotating coordinate system. For motors with low-speed rotors, the multi-variable, high-order, strong-coupling and nonlinear equation of motors was further transformed to a linear equation. However, it was found difficult to solve the deduced linear equation through the method of least squares due to its high singularity. The steady-state stator resistance could be predetermined by temperature revision on the stator resistant in the motor nameplate. Identification of four motor parameters (Ls,M, Rr, Lr) was followed by the recursive least-squares method. Simulations of motor parameter estimation were carried out in Simulink of Matlab. The recursive least-squares method was used to deal with the measured data. The results demonstrate that the real-time electrical parameters (Ls, σ, Tr) can be accurately predicted. Given the assumption of Ls = Lr in the classical motor theory, the other three electrical parameters (M, Rr, Lr) can also be identified. The identification of these parameters is of great importance for the analysis, control and fault diagnosis of induction motors.