Research On Online Identification Of SPMSM Parameters

Surface mount permanent magnet synchronous motor are widely used in various industries due to high power density,simple control methods and easy manufacturing.The study found the parameters of SPMSM are easily affected by temperature,magnetic saturation and other factors that change the control performance of the motor.For some industries that require high precision,such as medical robots,passenger cars,etc.,it is necessary to track the electrical parameters(Stator resistance_sR,AC/DC axis inductance L,magnetic chain?_f)that affect the motor control performance,and real-time update control algorithm program to make the SPMSM work in high precision and high reliability.This article mainly studies how to identify the electrical parameters of SPMSM with high accuracy.This paper describes the voltage and current state model of the SPMSM in the ABC,??,dq respectively.Several commonly used vector control algorithms such as id=0,MTPA,unit power factor,and field weakening control are introduced in detail.A vector control system is built in Matlab/Simulink to implement the SVPWM with id=0 control,and the simulation results verify the accuracy of the model.This article briefly describes the online parameter identification algorithms commonly used in SPMSM,and explains the advantages and disadvantages of various identification algorithms.Combining the complexity of online identification of motor parameters,this paper uses an improved genetic algorithm-anti-predator particle swarm algorithm(APSO)for SPMSM parameter online identification.Through several commonly used test functions,the convergence accuracy and convergence of APSO and standard PSO are compared.Simulation results show that APSO is superior and effective in dealing with single-peak problems similar to motor parameter identification.In addition,a comparative simulation experiment is performed on whether the parameter identification result is input to the PI controller for auto tuning to control performance.The experimental results also show the necessity of PI self-tuning.Finally,a surface permanent magnet synchronous motor controller based on the STM32f103c8t6 minimum system is designed.The experimental motor is a 4k W SPMSM.The effectiveness of the controller and the parameter identification ability are verified through a series of experiments.