具有参数辨识的永磁同步电机无位置传感器控制

转子磁极位置估计的准确性决定永磁同步电机无位置传感器控制系统的性能,为了实现转子位置和转速的精确控制,需要对电机参数进行在线辨识。根据实际冰箱制冷系统需求,采用模型参考自适应系统构建无位置传感器矢量控制方案,在仿真研究电机参数变化对位置估算影响的基础上,提出了一种具有参数辨识的内埋式永磁同步电机无位置传感器控制方案。利用电机的电流模型,运用扩展卡尔曼滤波器对转子磁链和交轴电感同时进行在线辨识,并将辨识出的参数用于更新无位置传感器矢量控制算法中的电机模型。仿真和实验结果表明,参数辨识算法可以有效地辨识出实际的转子磁链和交轴电感,具有参数辨识的无位置传感器矢量控制方案可行有效,在压缩机厂商提供的电机参数存在一定误差的情况下可以保证冰箱制冷系统的性能。

Sensorless Control of Permanent Magnet Synchronous Motor with Online Parameter Identification

The accuracy of the rotor position estimation determines the performance of the sensorless control system of permanent magnet synchronous motor (PMSM). In order to realize precise rotor position/speed control, motor parameters should be online identified. According to the requirements of practical refrigeration system, model reference adaptive system (MRAS) was used in building a sensorless vector control scheme. Then the influence of the changed motor parameters was simulated, and a sensorless control scheme with parameter identification of interior permanent magnet synchronous motor (IPMSM) was proposed. An extended Kalman filter (EKF) online identified the parameters of the rotor flux linkage and q-axis inductance based on the current model of IPMSM, subsequently the identified parameters updated motor model in the sensorless control algorithm. Simulation and experimental results show that the parameter identification algorithm can effectively identify the actual rotor flux linkage as well as q-axis inductance. The position sensorless vector control scheme combined with online parameter identification is feasible and effective, which guarantees the performance of the refrigeration system with some errors of the motor parameters provided by compressor manufacturers.