基于模型预测自适应的双绕组电机参数辨识技术  

Parameter Identification Technology of Dual Winding Motor Based on Model Reference Adaptive System

作　　者：白雪 毛峥 马相龙 BAI Xue;MAO Zheng;MA Xianglong(Shanghai Marine Equipment Research Institute,Shanghai 200031,China)

机构地区：[1]上海船舶设备研究所,上海200031

出　　处：《机电设备》2024年第6期58-64,69,共8页Mechanical and Electrical Equipment

摘　　要：针对双绕组无刷直流电机(DW-BLDCM)参数难以在线辨识的问题,设计一种基于模型预测自适应控制(MRAS)的双绕组无刷直流电机在线参数辨识算法。基于DW-BLDCM的理想相电流波形建立电机模型,消除了2组绕组之间的互感耦合,使参数辨识更准确。通过DW-BLDCM状态方程建立模型预测自适应模型,实现在线参数辨识。试验结果显示:电机相电感的辨识误差为3.33%,相电阻的辨识误差为3.70%。结果表明,基于MRAS的算法可实现DW-BLDCM的在线参数辨识。Aiming at the problem that it is difficult to identify the parameters of double winding brushless DC motor(DW-BLDCM)online,an online parameter identification algorithm of DW-BLDCM based on model predictive adaptive control(MRAS)is designed.Firstly,the motor model is established based on the ideal phase current waveform of DW-BDLCM,which eliminates the mutual inductance coupling between the tow groups of windings and makes the parameter identification more accurate.Then,the MRAS model is established through the state equation of DW-BLDCM to realize online parameter identification.The experimental results show that the identification error of motor phase inductance and phase resistance is 3.33%and 3.70%,respectively.The results show that the algorithm based on MRAS can realize the online parameter identification of DW-BLDCM.

关 键 词：双绕组无刷直流电机 在线参数辨识 模型预测自适应控制 

分 类 号：TM306[电气工程—电机]