Research On Sensorless Rotor Position Detection Of Permanent Magnet Synchronous Motor With Improved MRAS

The utilization of permanent magnet synchronous motors in military,aerospace and industrial production is significant due to their straightforward design,diminutive size,excellent dynamic performance,high efficiency,wide speed range and other attributes.To reduce the size and cost of motor drive systems,as well as enhance fault tolerance and environmental adaptability,researchers have given extensive consideration to the sensorless control technology of these motors.In the PMSM model,the stator resistance,stator inductance,rotor inductance,and permanent magnet flux linkage are all sensitive to nonlinear factors,such as magnetic circuit saturation,environmental temperature,and external interference,which can have an impact on the accuracy of the sensorless control algorithm’s positon estimation in the practical application of motors.Multi-parameter identification faces the problems of equation underrank,identification sequence,and initial parameter values.The difficulty of identifying motor parameters is greater especially when the motor operating speed is unknown.The significance and application prospects of in-depth research on parameter identification methods for permanent magnet synchronous motor models are immense.This article proposes an online multi-parameter identification strategy for sensorless control of such motor models.The main research content is as follows:Initially,two coordinate systems were investigated to analyze the mathematical models of permanent magnet synchronous motors.The basic control mechanisms of common vector control and direct torque control methods were analyzed.An examination of the influence of parameter discrepancy on system performance was conducted,taking into account the threeclosed-loop cascade control model of permanent magnet synchronous motors.The new electrical and dynamic equations were established.Laying the foundation for the parameter identification algorithm and sensorless control strategy optimization in subsequent chapters.Subsequently,the model’s reference adaptive algorithm’s construction and the adaptive law’s design technique were scrutinized.Taking into account the nonlinear and time-varying characteristics of the controlled object of permanent magnet synchronous motor,a model reference adaptive law based on Popov metastable theory is designed.A Popov metastable theory-based model reference adaptive online motor position identification study was constructed,and its simulation verification was done in MATLAB/Simulink.The effect of stator resistance,rotor inductance and rotor flux linkage of a permanent magnet synchronous motor on the identification of motor position by a model reference adaptive system was then analyzed.Then,a model reference adaptive step-by-step online identification strategy for the inductance,flux and resistance,and rotational inertia of a position sensorless permanent magnet synchronous motor was studied.Estimating the rotor position of the motor,a position sensorless control algorithm was implemented for the permanent magnet synchronous motor,based on the parameters identified.An improved model reference adaptive step-by-step multi-parameter online identification was the basis for the design and construction of an experimental platform for the permanent magnet synchronous motor control system,at long last.The hardware circuit was driven by TI’s dedicated motor control DSP chip TMS320F28335 as the core.The software mainly completed the Popov metastable theory reference model adaptive online multi-parameter distribution identification algorithm,permanent magnet synchronous motor position estimation,as well as current loop,speed loop,and position loop control functions.Verification of the proposed method’s feasibility and efficacy was achieved through simulations and experiments.