Permanent Magnet Synchronous Motor Loss Minimization Predictive Current Control

Efficiency has become an important index for evaluating the motor performance in the fields of oil exploration,steel processing,coal mining,etc.In recent years,the permanent magnet synchronous motor has been increasingly widely used in those fields,which makes the improvement of the motor materials,designs or improve the loss minimization control method became a research hotspot.However,the traditional loss minimization control method based on search technology has a slow convergence speed,and the traditional loss minimization control method based on loss model needs complex parameters off-line calculating work,and the parameter calculation error may affect its effect.In addition,the current tracking error in the traditional predictive current control method cased by neglecting the iron loss will also affect the energy saving effect of the traditional loss minimization predictive current control.This paper presents a novel loss minimization control method based on iron loss on-line calculation.The proposed method calculates the optimal d-axis current which can minimize the loss by the value of the iron loss and the flux modulus.A Kalman observer is designed to observe the stator current iron loss variable,and then the result is used to calculate the value of the iron loss and the flux modulus.To ensure the performance of the loss minimization algorithm,the stator current iron loss variable is introduced to the predictive current control,thus the current tracking errors caused by neglecting the iron loss can be eliminated.Finally,this paper builds an experimental platform of permanent magnet synchronous motor system to make an experimental research of the proposed methods.The experimental results show that the proposed predictive current control method has less current tracking error than the traditional method.And the proposed loss minimization method based on iron loss on-line calculation has a good control performance and a obvious energy saving ability.