Speed Sensorless Control Method For Permanent Magnet Synchronous Motor

With the modern motor technology devolop,permanent magnet synchronous motor(PMSM)has been more and more widely used in daily life with its many advantages,so it is very important to master the synchronous motor speed control method.The rotor's position and the speed are very important in the control system of the permanent magnet synchronous motor.To get the speed error and angle when doing a coordinate transformation,usually it is necessary to install sensors such as encoders or resolvers on the motor to obtain the rotor's position and speed's signals of the rotor.In recent years,sensorless control technology has become one of the research hotspots of permanent magnet synchronous motors.This article mainly introduces two methods about it:using high frequency injection method and using extended Kalman filter method(Extended Kalman Filter,EKF).In order to facilitate the design of the algorithm,this paper first ly proposes the related theory of coordinate transformation,and obtains a PMSM model based on various coordinate systems.It also introduces the theory of magnetic field orientation control,this theory is commonly used in motor speed's control-systems.Through control the current in the synchronous coordinates,we can decouple the system and make it be equivalent to DC-motor.The SVPWM technology was also introduced in the article,it provide stable and efficient effects in the motor 's system.It is an necessary part in the motor's system.In order to solve problem of the rotor's position estimation in the motor speed control system,the linear Kalman filter method is introduced firstly,and the basic equations are also proposed for discrete and continuous system.Through the linear Kalman filter equation,the nonlinear equation can be approximately obtained,and the extend Kalman filter equation can be also obtained.According to the obtained motor model in the synchronous coordinate,the sensorless control algorithm based on extended Kalman filter can be obtained.As the poor performance of the EKF observer at zero and low speed,the high frequency injection method is introduced in the article.This method requires an additional signal generator in the system,which increases cost and size.When the high-frequency signal passes the motor,it will carry the rotor 's information,and then use the filtering method to obtain the useful signal.Finally,through useing position tracking observer or PLL technology,we can get the rotor position information.Finally,according to the two methods proposed above,the system model is built in the Matlab/Simulink environment.The simulations of the extended Kalman filter and the high frequency injection algorithm are carried out respectively to verify the correctness and effectiveness of the two algorithms.