永磁同步电机永磁体状况在线监测

On-line Estimation of Permanent-magnet Flux Linkage Ripple for PMSM

提出一种基于卡尔曼滤波器的永磁同步电机永磁体磁场状况在线监测方法。通过选择磁场同步旋转坐标系下定子电流和永磁体磁链为状态变量,构建估算转子永磁体磁链幅值和方向的卡尔曼滤波器。该方法能准确跟踪永磁体真实状况,对电机参数不敏感,鲁棒性强。基于动态估算的电机永磁体磁链,可为永磁同步电机控制系统实时提供准确的转子磁链信息,提高系统控制性能和效率。同时,基于永磁体磁场状况的动态监测,可防止永磁电机失磁状况的恶化,降低不可逆失磁程度,提高系统可靠性。实验结果验证了方法的正确性和有效性。

A new on-line permanent magnet flux linkage identification method for PMSM is presented to reduce the negative influence caused by demagnetization or position feed-back error. To estimate flux magnitude and direction, a Kalman filter is built by using stator current and PM flux as state variables under magnetic field oriented coordinate. The estimation method can accurately track the diversity of permanent flux and is robust to motors＇ parameters. Permanent flux based on dynamic estimation can offer real-time accurate rotor flux information, which can obviously improve the control performance and efficiency of PMSM. The dynamic estimating method can also prevent deterioration of demagnetization. Experiment results verify the effect of this method.