Neuro-Fuzzy Approach on Core Resistance Estimation at Loss Minimization Control of Permanent Magnet Synchronous Motor

Abstract

Iron losses are among the most significant losses occurring on the Permanent Magnet Synchronous Motor (PMSM). These losses consume active power and cause heat in the iron core. Due to this behavior, they can be represented by an equivalent resistance to make the computations simple. Determining the equivalent core resistance is also a major problem. Computing these lost power is very difficult especially in dynamic applications because these lost power varies by partial differential equations. This study aims to estimate the dynamic core resistance depended on inconstant operating conditions online, and compare the performance of the motor with dynamic versus fixed core resistance at the designed loss minimization algorithm. In order to obtain this estimation, firstly the finite element calculations have been made for many different operating speeds and lost power values were gathered for each speed. Then corresponding core resistance for each power value has been calculated with the dynamic model of a PMSM. Finally, a Neuro-Fuzzy estimator has been designed by computations on the gathered resistance values to estimate the core resistance for different operating conditions. At the end the obtained results are discussed with respect to feasibility of the system.