基于开关模型参数辨识的IPMSM优化MTPA控制策略

IPMSM Optimization of MTPA Control Strategy Based on Switching Model Parameter Identification

摘要: 针对由于实际电机运行过程中因为参数变化而导致MTPA控制不能获得最大转矩电流比的问题。在同步旋转坐标系dq轴建立PMSM满秩辨识开关模型，将dq轴电流的微分量利用采样器将有效矢量和零矢量作用的电流采样作为输入分为三次辨识MTPA控制需要的dq轴电感和磁链。提出一种基于PMSM开关模型利用递推最小二乘法(RLS)来在线辨识电机实际运行参数在反馈回MTPA控制算法中，来对其参数进行修正，降低相同转矩下的定子电流值。并与模型参考自适应参数辨识法比较。经仿真结果表明，该方法能更有效地降低相同转矩下的定子电流值。

Abstract: Aiming at the problem that the MTPA control can not obtain the maximum torque-current ratio due to the parameter change during the actual motor operation. The PMSM full-rank identification switch model is established in the synchronous rotating coordinate system dq axis, and the micro-components of dq axis current are divided into three identification of dq axis inductance and flux linkage required by MTPA control by using sampler and current sampling of effective vector and zero vector as input. Based on the PMSM switching model, a recursive least square method (RLS) is proposed to identify the actual operating parameters of the motor online and modify the parameters in the feedback MTPA control algorithm to reduce the stator current value under the same torque. It is compared with the model reference adaptive parameter identification method. The simulation results show that the proposed method can reduce the stator current value at the same torque more effectively.