摘要
随着科技与工业化的迅猛发展,永磁同步电机(PMSM)的性能要求变得更加严格,而高性能的PMSM控制系统主要依赖于高精度的传感器和精确的检测技术。因此,为了实现低成本、高精度与高可靠性的电机控制系统,开展了基于扩展卡尔曼滤波(EKF)的无速度传感器控制方法研究。建立了PMSM的数学模型,并根据EKF算法实现了对PMSM的转子速度和位置的高精度估计。通过Simulink开展了永磁同步电机无速度传感器的EKF数值模拟试验,并分析了PMSM参数的变化对EKF估计效果的影响。结果表明,EKF设计的观测器能够很好地跟踪转子的转速和转子的电角度,验证了无速度传感器和扩展卡尔曼滤波的有效性;当定子电阻参数变化时,转矩的变化对观测的精确度影响更敏感;当转子磁链的值不准确时,估值的精度对转速的变化更为敏感。
With the rapid advancement of technology and industrialization,the performance requirements for Permanent Magnet Synchronous Motors(PMSM)have become increasingly stringent.High-performance PMSM control systems primarily rely on high-precision sensors and accurate detection technologies.Therefore,to achieve a low-cost,high-precision and highly reliable motor control system,a sensorless speed control method based on the Extended Kalman Filter(EKF)is investigated.A mathematical model of PMSM is established,and the EKF algorithm is applied to achieve high-precision estimation of rotor speed and position.A numerical simulation experiment of PMSM sensorless control using EKF is conducted in Simulink,and the influence of PMSM parameter variations on EKF estimation accuracy is analyzed.The results demonstrate that the EKF-based observer effectively tracks the rotor speed and electrical angle,verifying the feasibility of sensorless control and the effectiveness of the EKF algorithm.Moreover,when the stator resistance parameter varies,torque fluctuations have a more significant impact on estimation accuracy.When the value of the rotor flux is not accurate,the accuracy of the estimation is more sensitive to the change of the speed.
作者
宋崇耀
SONG Chongyao(China Railway Construction Tongguan Investment Co.,Ltd.)
出处
《现代矿业》
2025年第4期202-207,212,共7页
Modern Mining
关键词
扩展卡尔曼滤波算法
永磁同步电机
无速度传感器控制
extended Kalman Filter Algorithm
permanent magnet synchronous motor
sensorless speed control
