Rotor Position Estimation Of Sensorless Permanent Magnet Synchronous Motor Based On Two Stage Extended Kalman Filtering Algorithm

Permanent magnet synchronous motor(Parameter Magnet Synchronous Motor,PMSM)with its simple structure,safe and reliable,good dynamic performance,the characteristics of good speed performance is widely used in electric vehicles,marine power and aerospace and other important areas.In high performance motor control applications,to obtain the rotor position information is essential,but the traditional position sensor technology because of its defects and the influence of the external environment will be the sensorless control technology to replace,become the focus of current research.The extended Kalman filter algorithm has been widely applied in no position sensor control technology,but it has a large amount of computation,high requirements for hardware problems.In order to solve this problem in this paper.A permanent magnet synchronous motor vector control a two segment extended Kalman filter algorithm,the algorithm is in the original extended Kalman filter(Extended Kal Man Filter,EKF)on the basis of the split into two low order filter run in parallel,but both are mathematically equivalent.The experimental results show that the estimation performance of the algorithm can not only achieve the original EKF algorithm,and compared to the original EKF algorithm reduces the total computation,shortening the operation time.This paper first introduces the research status and development direction of PMSM speed control system,describes the basic structure of PMSM,and introduces the principle of coordinate transformation for the vector control of PMSM laid the foundation,then the mathematical model in different coordinates is PMSM,after the study of the permanent magnet synchronous motor control method and the main commonly used algorithm for speed sensor control,comparing the advantages and disadvantages of various algorithms.Aiming at the nonlinear,permanent magnet synchronous motor characteristics of strong coupling,complex operation,control the use of voltage space vector pulse width modulation technology,and the simulation platform is built with PMSM simulation of speed sensorless vector control.Then it introduces the basic principle of EKF algorithm,and the algorithm is analyzed,the paper presents the algorithm flow chart.Use this algorithm to design the extended Kalman filter observer,and based on speed sensor simulation model is built based on permanent magnet synchronous electric machine EKF algorithm of speed sensorless control system simulation model in PMSM,through the feasibility analysis andsimulation proved that the algorithm is correct and effective.At the same time,the PI controller in the vector control of the improved reduced system estimates the overshoot and improve the stability of the system.Finally,in order to solve the traditional arithmetic extended Kalman filter algorithm in large quantity,high requirements for hardware problems.This paper presents an improved two stage extended Kalman filter algorithm(Two Section Extended Kalman Filter,TSEKF),the algorithm into two low order filters for parallel operation based on the original extended Kalman filter algorithm on the split,but both are mathematically equivalent.At the same time,a TSEKF simulation model is built,the experimental results show that the estimation performance of the algorithm can not only achieve the original EKF algorithm,and compared to the original EKF algorithm reduces the total computation time,shorten the operation time.