Research On Predictive Current Control Of PMSM Drive System

Permanent magnetism synchronous machine is widely used in aerospace,high speed rail,national defense,advanced rail transportation,new energy vehicles and other key fields because of its small size,stable and reliable operation and low maintenance cost in recent years.As the core of PM synchronous motor drive system,the control strategy has a very important impact on the operation performance of Permanent magnet synchronous motor drive system,however,the most commonly used linear control scheme is still inadequate in the face of multivariable,strong coupling and other nonlinear characteristics of PM synchronous motor.However,there are still some problems to be solved in the existing model predictive control in terms of parameter robustness and steady-state accuracy.In this thesis,we take the two-level PMSM drive system as the research object and carry out the research on the predictive current control of PMSM drive system.Based on the mathematical model of PMSM system,this thesis describes the implementation process of model predictive control in PMSM drive system in detail,and the sensitivity analysis of traditional PMSM predictive control in terms of inductance,resistance and magnetic chain is carried out to confirm that the existence of parameter mismatch will lead to predictive control with The sensitivity analysis of the conventional PMSM prediction control was conducted in terms of inductance,resistance and magnetic chain,respectively.To solve the above problems,a robust model predictive control method based on Extended State Observer(ESO)is proposed;the effect of magnetic chain parameter mismatch is eliminated by introducing an incremental model,and an ESO-based inductor perturbation observer is designed to reduce the effect of inductor parameter mismatch,which further improves the parameter robustness of the PMSM drive system.Finally,the effectiveness of the proposed strategy is verified by simulation.In order to further improve the steady-state control accuracy of PMSM predictive control,take into account the simplification of algorithm and robustness of system parameters,a PMSM fast dual-vector model-free predictive control method is proposed in this thesis,which firstly replaces the original current differential equation by establishing a hyperlocal model of the PMSM drive system,thus freeing the system from the influence of motor parameters.After that,the fast vector selection method is combined with the dual vector control method,and the first optimal voltage vector selection method is used to simplify the system calculation,and at the same time,the range of the original vector selection is increased by using the dual vector control strategy,thus improving the steady-state control accuracy.Finally,the simulation study in MATLAB/Simulink confirms that the proposed control method has good antiparameter disturbance capability and good dynamic steady-state characteristics.Finally,the proposed control strategy is verified by building an experimental platform for two-level PMSM drive system,and the effectiveness of the proposed control strategy is confirmed by the corresponding experimental analysis in terms of dynamic steady state and parameter robustness.There are 54 figures,12 tables and 98 references in this thesis.