인공 신경망을 이용한 PMSM의 MTPA 운전점 개선

Abstract

In order to minimize copper loss of Permanent Magnet Synchronous Motor(PMSM), Maximum Torque Per Ampere(MTPA) control is essential. The MTPA control method utilizing mathematical models requires accurate information of parameters, but it is difficult to perform an accurate MTPA because the parameters may vary with temperature and load. Therefore, this paper proposes the new MTPA control method using ADALINE(Adaptive Linear Neuron), one of the Artificial Neural Network(ANN). In the proposed method, the locus of the stator current relative to the dSUPγ/SUP -axis current is estimated using ADALINE, and the MTPA operating point is determined through the estimated locus. This method is resistant to fluctuations in motor parameters and is easy to implement.