Research Based On The Cubature Kalman Filter Of Speed Sensorless Vector Control Of Asynchronous Motor

Asynchronous motor speed sensorless vector control technology is widely used in the field of motor control.Among the various sensorless control methods,Kalman filter has been the focus of the research on the speed estimation of asynchronous motor,which has the advantages of simple method,strong implementation,fast convergence and strong anti noise ability.However,when the traditional Extended Kalman filter(EKF)method is used to linearize the nonlinear system equations,the method is to ignore the higher order terms,and the filtering precision is reduced.Therefore,in order to improve the accuracy,the method needs to be further improved.Based on the analysis of the traditional EKF method,this paper proposes an improved Kalman filtering method-Cubture Kalman filter to estimate the speed of motor.The main contents of the study are:First of all,vector control technology is one of the most commonly used control technology in modern high performance AC motor speed control technology,so the vector control system is used in this paper as the basis of the speed control algorithm.The simulation model of vector control system of asynchronous motor is established through the study of the theoretical knowledge of motor and the analysis of vector control technology.The simulation results show that the method is convenient,reliable and effective,and provides a theoretical basis for further research on the sensorless vector control system of asynchronous motor.Secondly,based on the vector control system of asynchronous motor,the extended Kalman filter(EKF)algorithm is used to study the speed sensorless vector control of the motor.The model of speed sensorless vector control system based on EKF is established by using Matlab/Simulink.Compared with the actual running state of the motor,The simulation results show that the EKF algorithm has good estimation performance,and the tracking performance is ideal.It also verifies the accuracy and feasibility of the speed sensorless vector control algorithm.Thirdly,the EKF method needs to linearize the model and calculate the Jacobian matrix,which can lead to the problem of large amount of computation in the speed estimation,short sampling period required and difficult practical application.In order to overcome these shortcomings,a new Kalman filtering method called Cubature Kalman Filter algorithm is studied in this paper.In this paper,the principle of Cubature Kalman Filter algorithm is introduced and applied to the vector control system of motor.Then,the simulation model of asynchronous motor speed sensorless control system based on CKF is built.The simulation in low speed,medium speed and high speed verify the estimation effect.And compare estimation effect of the system with the Extended Kalman Filter algorithm when conducting the dynamic estimation.The simulation results show that the system has better tracking performance,and the estimation performance is better when the speed is low.The system can improve the speed estimation effect evidently.Finally,this paper uses DSP(F2812)development system to design the experiment.Through the design of the hardware and software of the system,the experiment platform of the speed sensorless vector control of asynchronous motor based on CKF is established.In the aspect of hardware,this article designs rectifier filter circuit and IPM inverter circuit and so on.In the aspect of software design,this paper applies the method of automatic generation of DSP code based on MATLAB/Simulink.The paper completes the complex function of the DSP program design by Simulink.Finally to match the hardware design,the design of experiments is completed,and the experiment has been carried on successfully.The experimental results show that it is feasible for the Cubature Kalman Filter algorithm to estimate the flux and speed,achieving the desired results.It can provide some reference for the research of asynchronous motor control system.