Design of Motor Observer with Iron Loss and Parameter Identification

Abstract

The efficiency optimization control method based on loss model has the advantages of clear physical meaning and fast optimization speed. However, this method is sensitive to the real-time parameters of the motor in the model. To improve the observation effect, it is necessary to accurately obtain the real-time parameters of the motor in the loss model. By designing a stable adaptive law, the key parameters in the loss model are identified adaptively; In order to improve the observing speed and robustness of the state observer for induction motor, the pole placement of the feedback matrix with iron loss is carried out; In order to improve the performance of the algorithm, an adaptive identification algorithm for key parameters is designed according to the stability law, and the theory is verified by simulation.