Research On Speed Sensorless Vector Control System Of Asynchronous Motor

With the continuous development of electric vehicles,the requirements for the control performance of automotive motors are constantly increasing.Compared with synchronous motors,asynchronous motors(IM)have the advantages of simple structure,low cost and environmental friendliness.Vector control is the mainstream method for controlling asynchronous motors.The core of vector control algorithms is to obtain the motor speed information.However,the installation speed sensor is costly and the reliability of the acquisition speed is greatly affected by environmental factors.Therefore,this paper will focus on the speed sensorless vector control technology of asynchronous motor,and make an in-depth analysis of the speed identification.Firstly,using the principle of electrical engineering,the principle of coordinate transformation of equivalent motor vector is explored,and the mathematical model of asynchronous motor is simplified.In-depth understanding of the vector control method based on the rotor field orientation to achieve complete decoupling of excitation and torque.In order to study the asynchronous motor speed sensorless vector control system and the speed identification in the speed sensor,the theoretical basis is laid.Based on the theoretical basis,the classic MRAS speed identification system was established.Taking the voltage-current model of the asynchronous motor as the reference model,the current-speed model is used as the adjustable model,and the rotational speed is set to the adjustable variable.The adaptive law of the classical MRAS is established by the Popov hyperstability theory.However,the pure integral link existing in the classic MRAS speed identification system will lead to error accumulation in the speed estimation,especially affecting the speed identification ability at low speed,which further affects the speed regulation performance of the asynchronous motor speed sensorless vector control system.This paper establishes the classic MRAS speed identification system.Taking the voltage-current model of the asynchronous motor as the reference model,the current-speed model is used as the adjustable model,and the rotational speed is set to the adjustable variable.The adaptive law of the classical MRAS is established by the Popov hyperstability theory.However,the research finds that the pure integral link in the classic MRAS speed identification system will affect its speed identification capability,and further affect the speed regulation performance of the asynchronous motor speed sensorless vector control system.Therefore,this paper proposes a new MRAS rotational speed identification system based on discrete finite set model predictive control(FCS-MPC).The system innovatively uses the phase difference of the stator and rotor coordinate system as an adjustable variable,and introduces the vector transformation in the fixed and rotor coordinate systems in the adjustable model.The system uses an iterative search optimization mechanism to discretize the possible positions of the rotor to find the optimal rotor position that minimizes the cost function value.And through the optimization mechanism to achieve online update,the motor rotation speed calculation with the optimal rotor position change,the speed calculation with limited data acquisition,improve the speed identification ability of the classic MRAS method.Finally,the improved MRAS speed identification system is combined with the asynchronous motor vector control system,and the simulation model is built on the MATLAB/Simulink platform for simulation analysis.The simulation results show that the speed identification ability of the designed MPC-MRAS speed identification system is better than the traditional MRAS speed identification system.The speed control performance of the speed sensorless vector control system based on the speed identification system is more stable and reliable.The program is indeed effective and feasible,with the value and potential for further experimental research.