Constrained Minimization for Parameter Estimation of Induction Motors in Saturated and Unsaturated Conditions

This paper presents the analytical solution of the application of the constrained least-squares (LS) minimization to the online parameter estimation of induction machines. This constrained minimization is derived from the classical linear dynamical model of the induction machine, and therefore it is able to estimated the steady-state value of the electrical parameters of the induction motor under different magnetization levels. The methodology has been verified in simulation with a dynamical model which takes into account iron path saturation effects. After a description of the experimental setup and its signal processing systems, the methodology is verified experimentally under saturated and unsaturated working conditions, and the results are discussed and compared to those obtained with a classical unconstrained ordinary LS technique.