Research On Sensorless Compound Control Method Of Permanent Magnet Synchronous Motor In Wide Speed Range

Permanent Magnet Synchronous Motor(PMSM)has been widely used in the field of new energy vehicles due to its advantages of high efficiency,non-polarity,strong stability,long life and low maintenance cost.Traditional position sensors intensify the electronic control The complexity of the system,and the sensorless technology can effectively simplify the structure of the control system,reduce hardware costs and improve system reliability.Therefore,in order to solve the problems of low observation accuracy in traditional sensorless control strategies and the difficulty in achieving accurate observations in a wide speed range,this thesis studies the sensorless control strategy of permanent magnet synchronous motors in a wide speed range.Aiming at the observation chattering existing in the traditional sliding mode observer in the medium and high speed domain and the observation phase delay caused by the traditional low-pass filter,a non-singular terminal sliding mode adaptive observer is proposed in this thesis.Firstly,the back EMF of the motor is estimated by combining the non-singular terminal sliding mode surface with the exponential reaching law,which eliminates the singularity of the system and effectively suppresses system chattering.Secondly,an adaptive filter is designed to replace the traditional low-pass filter to effectively reduce the Estimate latency and further improve estimation accuracy.At the same time,this thesis compares the structure and estimation accuracy of the stationary shafting biaxial high-frequency injection method and the synchronous shafting single-axis high-frequency injection method in the low-speed region interval.After analysis,it is concluded that the synchronous shafting single-axis injection method has a smaller calculation amount.The conclusion that the same accuracy as the stationary shafting biaxial injection method is achieved,and the correctness of the conclusion is verified by simulation and experiment.In order to realize the smooth transition from the low-speed stage to the high-speed stage,this thesis proposes a non-linear weighted compound control strategy based on BP neural network to solve the problem of serious decline in estimation accuracy caused by traditional switching algorithms.First,a new nonlinear weighted switching strategy is proposed,which uses the parameter adjustability of the nonlinear curve to make the switching process of the system more stable in the transition zone,and effectively reduces the motor speed error;secondly,for the partition-less positionless algorithm To solve the problem that the accuracy changes are complex and difficult to determine,a neural network algorithm based on system error is proposed to correct the parameter values of the switching function,which further suppresses the position estimation error of the system and improves the smoothness of the switching process.In order to verify the feasibility of the design strategy in this thesis,a control experiment platform based on permanent magnet synchronous motor is built.The experimental results show that the sensorless control strategy designed in this thesis can effectively improve the estimation accuracy and stability of the system in a wide speed range,and achieve the expected goal of this thesis.