基于REKF的永磁同步电机无传感器控制研究

发布时间：2018-05-13 04:23

本文选题：永磁同步电机 + 无传感器　；参考：《河南理工大学》2014年硕士论文

【摘要】：电机驱动系统在现代工业生产中具有重要地位,其正朝着高精度、宽调速范围、高速方向发展。目前,鉴于永磁同步电机结构简单、体积小、损耗小、调速性能好、功率密度高和可靠性高等优点,其逐步发展为电机驱动系统中的主流电机。带有位置或速度传感器的电机驱动系统不仅增加成本,降低可靠性,而且对使用环境也有严格要求,限制了电机的使用范围,因此永磁同步电机无传感器控制逐渐成为研究的热点。本文主要研究基于衰减因子和补偿函数的降阶扩展卡尔曼滤波算法的永磁同步电机无传感器控制。鉴于扩展卡尔曼滤波算法存在运算量大,实时性差等问题,提出降阶扩展卡尔曼滤波算法,通过适当选取状态变量,将状态转移矩阵降为三阶矩阵,简化滤波器结构,提高运算速度;结合衰减记忆滤波法选取衰减因子,有效提高电机估计转速跟踪实际转速的快速性,进一步改善该算法的跟踪性能;对估计转角进行转速和电流补偿,提高转角估计的精度。最后搭建该控制系统模型和S函数,并验证结合衰减记忆滤波法和补偿函数的降阶扩展卡尔曼滤波算法在该控制系统中的可行性和有效性,通过仿真试验结果可知,系统最佳衰减因子为s=1.01。
[Abstract]:Motor drive system plays an important role in modern industrial production. It is developing towards high precision, wide speed range and high speed. At present, permanent magnet synchronous motor (PMSM) has been developed into the mainstream motor in motor drive system because of its simple structure, small volume, small loss, good speed regulation performance, high power density and high reliability. The motor drive system with position or speed sensor not only increases the cost and reduces the reliability, but also has strict requirements for the operating environment, which limits the range of use of the motor. Therefore, sensorless control of permanent magnet synchronous motor (PMSM) has gradually become a hot research topic. This paper focuses on sensorless control of PMSM based on reduced order extended Kalman filter algorithm based on attenuation factor and compensation function. In view of the problems of large computation and poor real-time performance in the extended Kalman filter algorithm, a reduced order extended Kalman filter algorithm is proposed. By properly selecting state variables, the state transfer matrix is reduced to the third order matrix, and the filter structure is simplified. Improve the speed of operation, select attenuation factor with the method of attenuated memory filter, effectively improve the speed of the motor speed tracking, further improve the tracking performance of the algorithm, and compensate the speed and current of the estimated rotation angle. Improve the accuracy of angle estimation. Finally, the model and S function of the control system are built, and the feasibility and effectiveness of the reduced order extended Kalman filter algorithm combined with the attenuated memory filter and the compensation function in the control system are verified. The optimum attenuation factor of the system is sl. 01.
【学位授予单位】：河南理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM341

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