| Permanent Magnet Synchronous Motor(PMSM)is widely used in industrial production and daily life by virtue of its high efficiency and high power density.The traditional permanent magnet synchronous motor speed control system mostly adopts the speed and current double closed-loop vector control structure,but the sensor used to detect the rotor position and speed in the speed control system increases the system volume and cost,and the detection accuracy is easily affected by the installation environment.It’s difficult for Permanent Magnet Synchronous Motor to adapt to different working environments.At the same time,due to the dead zone characteristics of the inverter in the vector control system and the air gap harmonic magnetic field distortion effect when the motor is running,the stator three-phase current of the motor has 5th,7th and other high-order harmonic components.Under the action of the rotor permanent magnet,the electromagnetic torque fluctuates greatly,which reduces the stability and reliability of the system.In this context,the sensorless method of permanent magnet synchronous motor is used to detect rotor information and the suppression of torque periodic pulsation.The main contents are as follows:First,analyze the basic structure and theoretical model of permanent magnet synchronous motors,including the mathematical equations in the three-phase static coordinate system and the synchronous rotating coordinate system.Based on the basic principles of coordinate transformation,three-phase stationary-stationary two-phase transformation(Clarke)and inverse transformation and stationary two-phase-rotating orthogonal transformation(Park)and inverse transformation matrices are given.Combined with the more mature voltage space vector control strategy,the speed and current double closed-loop vector control structure model is established.Secondly,in order to solve the problem of detecting rotor information by sensorless method in the speed regulation system of permanent magnet synchronous motor,the extended Kalman filter is used to estimate rotor speed and position based on the infrastructure of double closed-loop vector control of speed and current,instead of the detection device used to calculate the speed and rotor position.And extended kalman filter in filtering divergence and estimates the results in the process of estimating the problem of insufficient accuracy,design an adaptive fading extended kalman filter estimation algorithm,based on the observation data of the new interest rates and the statistical characteristic of residual correction online measurement noise covariance matrix,at the same time,according to the theory of new interest selection matrix fading factor correction prediction error covariance matrix,makes the error covariance matrix order times each channel has a corresponding adaptive fading ability.Through the simulation analysis,the rotor information estimation algorithm can effectively suppress the divergence phenomenon in the estimation process,and improve the estimation accuracy.Finally,in the double closed loop speed current sensorless vector control structure based on the nonlinear characteristics of inverter and breath harmonic torque ripple caused by the magnetic field distortion effect,put forward a kind of open closed loop PID type iterative learning controller based torque ripple suppression method,the output of the speed loop and the system output torque of the real-time error compensation by iterative learning to shaft current for a given value.At the same time,an improved particle swarm optimization algorithm was designed to optimize and tune four key parameters of the iterative learning controller to improve the performance of the iterative learning controller and obtain the ideal torque ripple suppression effect.Simulation and experimental analysis show that the torque ripple suppression strategy based on iterative learning controller can effectively reduce the higher harmonic content in three-phase current and reduce the amplitude of torque ripple. |