Research On PMSM Model Predictive Control System Based On Sliding Mode Observer

With the rapid development of the automobile industry,the increasing number of automobiles in the world,the shortage of energy facing humanity,global warming,atmospheric pollution and many other issues have promoted the innovation and development of automobile technology.New energy electric vehicles have the characteristics of energy saving,environmental protection and sustainable development,and have become the development trend of the automobile industry.Permanent Magnet Synchronous Machine(PMSM)has high efficiency,high power factor,high power density,high torque-current ratio and low moment of inertia.It is used in electric vehicles of major automobile manufacturers at home and abroad.The motor is widely used.With the development of high-performance control technology,Model Predictive Control(MPC),as an advanced control method,has the characteristics of simple control idea,dynamic optimal control and strong adaptability to deal with nonlinear constraints.In recent years,the model predictive control method has more research and application in the control of permanent magnet synchronous motors.This paper takes three-phase permanent magnet synchronous motor as the research object,based on the model predictive control system theory,and uses the sliding mode observer(SMO)control method to study the model predictive current control and position sensorless of permanent magnet synchronous motor.The control method combined with the control performance of driving permanent magnet synchronous motor,designed a permanent magnet synchronous motor drive controller based on sliding mode observer and model predictive control control strategy.The main research contents are as follows:(1)The structure of permanent magnet synchronous motor is explained.Mathematical models of permanent magnet synchronous motors in different coordinate systems were established,that is,the mathematical models in three-phase stationary coordinate system,two-phase stationary coordinate system and two-phase synchronous rotating coordinate system,which laid the foundation for the subsequent study of PMSM control strategies and control algorithms basis.(2)The control strategy principle of model predictive control is introduced in detail.The predictive model,rolling optimization and feedback correction in MPC are introduced in detail,and the specific implementation method of model predictive current control in permanent magnet synchronous motor is studied.In Matlab/Simulink,the control strategy of model predictive current control is simulated,and the simulation results are analyzed in depth.(3)For the motor control system where the position sensorless technology is mostly used for vector control and direct torque control,the research combined with MPC is rare.The position sensorless technology suitable for MPC is studied.In this paper,the sliding mode observer control algorithm is used to design the sliding mode observer to obtain the speed and rotor position information of the motor during operation.The motor control is achieved by combining with the MPC control strategy.Through simulation,the effectiveness of the combination of position sensorless control algorithm based on sliding mode observer and model predictive control is verified.(4)The hardware and software system of the permanent magnet synchronous motor test platform is built,and the hardware circuit of the permanent magnet synchronous motor control system is designed,which mainly includes: selection of the main control chip,drive circuit,signal detection circuit,communication circuit and power supply circuit.The software control algorithm is compiled,and the software system design such as the operation of the sliding mode observer,the operation of the model prediction current control and the generation of the corresponding motor control signals are completed.On the basis of the complete design of the software and hardware,the corresponding experiments are carried out on the control system of the permanent magnet synchronous motor of the electric vehicle.The experiments verify the effectiveness of the proposed method.