基于Hammerstein模型的永磁同步电机EPS建模研究  

Research on Modeling of Permanent Magnet Synchronous Motor EPS Based on Hammerstein Model

作　　者：朱鑫健 沈泽宇 陈刚 宋国强 杜思伟 ZHU Xinjian;SHEN Zeyu;CHEN Gang;SONG Guoqiang;DU Siwei(Shanghai Xingyu Zhixing Technology Co.,Ltd.,Shanghai 201100,China)

机构地区：[1]上海星宇智行技术有限公司,上海201100

出　　处：《汽车零部件》2024年第12期82-87,共6页Automobile Parts

摘　　要：针对电动助力转向(EPS)系统中永磁同步电机(PMSM)系统的高精度建模需求,采用基于Hammerstein模型的辨识方法。将可分离信号与实际电机的q轴电压组合信号作为模型输入,构建基于Hammerstein模型的数据驱动模型,将可分离信号经过标称模型的输出与实际电机的q轴电流作为模型输出。基于这些输入和输出数据,采用相关分析法和泰勒级数展开方法分步辨识Hammerstein模型中的静态非线性子系统和动态线性子系统的参数。仿真结果表明,该方法能够有效辨识基于Hammerstein模型的永磁同步电机EPS系统,为智能驾驶中EPS系统的精确控制提供了理论基础。Focusing on the high-precision modeling requirements of permanent magnet synchronous motor(PMSM)system in electric power steering(EPS)systems,using a modeling and identification method based on the Hammerstein model.The combined signal of separable signals and the qaxis voltage of the actual motor is used as the model input to construct a data-driven model based on the Hammerstein model.The separable signals are output by the nominal model and the q-axis current of the actual motor as the model output.Based on these input and output data,the parameters of the static nonlinear subsystem and the dynamic linear subsystem in the Hammerstein model are identified using correlation analysis and auxiliary model probability density function methods,respectively.The simulation results show that the method proposed in this study can effectively identify the permanent magnet synchronous motor EPS system based on the Hammerstein model,providing a theoretical basis for precise control of EPS in intelligent driving.

关 键 词：HAMMERSTEIN模型 永磁同步电机 神经模糊网络 电动助力转向系统 

分 类 号：U463.4[机械工程—车辆工程]