GA-Based Off-Line Parameter Estimation of the Induction Motor Model Including Magnetic Saturation and Iron Losses

Abstract

This paper, starting from recent papers in the scientific literature dealing with Rotating Induction Motor (RIM) dynamic modelling, as a first step, improves its space-vector dynamic model, including both the magnetic saturation and iron losses; The main original aspects of the proposed model are the following: 1) the magnetic saturation of the iron core has been described on the basis of both current versus flux and flux versus current functions, 3) it includes the iron losses, separating them in hysteresis and eddy current ones, 4) it includes the effect of the load on the magnetic saturation. Afterwards, it proposes an off-line technique for the estimation of electrical parameters of this model, which is based on Genetic Algorithms (GA). The proposed method is based on input-output measurements and needs neither the machine design geometrical data nor a Finite Element Analysis (FEA) of the machine. It focuses on the application of an algorithm based on the minimization of a suitable cost function depending on the stator current error. The proposed electrical parameters estimation method has been initially tested in numerical simulation and further verified experimentally on a suitably developed test set-up.

Keywords

• Identification
• iron losses
• magnetic saturation
• parameter estimation
• rotating induction motor (rim)
• space-vector dynamic model