Minimum loss control at permanent magnet synchronous motors

In this study, which is on the basis of the minimizing methods of the electrical losses of Permanent Magnet Synchronous Motor (PMSM), primarily a research ran through detection, analysis and minimizing methods about electrical losses at PMSM. As a result to this research, the major problems on determination iron core resistance, which is the most important component for the analysis at loss control procedures, are identified, so a new and practical method to overcome these difficulties have been proposed. and proposed new methods of these processes. In this context, the iron core resistance, which is the basis for creating lost control algorithms in PMSM, calculated quite successfully using the combination of the Finite Element Method (FEM) and intelligent systems. To investigate the effect of the dynamic iron core resistance, a comparison made between the lossless PMSM model, in which the core resistance neglected, and the model with dynamic core resistance. Then, to determine the errors that may occur when taking iron core resistance fixed, models with dynamic and fixed iron core resistance were compared. As a result of this comparisons, it has shown that misleading results will be obtained if the variation of the dynamic iron core resistance is ignored. After establishing the importance of the dynamic core resistance in loss minimization applications, detailed loss minimization algorithms have been applied to created SMSM loss model which contains the dynamic core resistance. In this context, at first an analytical loss minimization method, which is a combination of Maximum Torque Per Ampere (MTPA) and Field Weakening (FW) control methods, was applied to the PMSM loss model. Finally, intelligent loss control algorithms that designed based on Neuro-Fuzzy and Neural Network systems applied to the PMSM loss model as two alternative loss minimization methods. So all the obtained results were examined.