Error Suppression Strategy Of PMSM Rotor Position Observation Based On Parameter Identification

Permanent magnet synchronous motor(PMSM)has been widely applicated in electric vehicles,industrial transmission and other fields due to its large torque density,high power factor and high reliability.The position information required by high performance vector control of PMSM is usually obtained by mechanical position sensor.The use of high precision position sensor will increase the volume and cost of the system,which is limited in harsh environment,and the reliability of the system is reduced.Among them,the research on sensorless control technology of permanent magnet synchronous motor has become a hotspot in recent years because of its cost reduction and strong robustness.The position observation method of back electromotive force(EMF)observer is widely used in middle and high speed sensorless control.But the observer is sensitive to motor parameters,and the influence of parameter mismatch on position estimation accuracy cannot be ignored.In addition,the nonlinearity of the inverter and the inaccuracy of current sampling lead to the existence of 6k ±1 harmonic and DC bias in the observed extended back EMF,which leads to the obvious pulsation in the estimated position,resulting in torque and current fluctuations,and reduces the PMSM sensorless control performance.To solve the above problems,this paper studies the rotor position observation error suppression strategy based on online parameter identification for the interior PMSM.First,the rotor position observation method based on parameter identification is studied.A position observation method based on PI extended back EMF observer and phase-locked loop model is described in detail,the influence of parameter changes on the estimation of back EMF and rotor position observation is analyzed,and Adaline neural network was used to modify the parameters of the observer in real time to improve the robustness of sensorless control.The algorithm has simple operation and accurate identification.On this basis,we put forward the normalized least mean square algorithm variable step size to provide weights updated,and this scheme improves the traditional fixed step size least mean square algorithm the characteristics of slow convergence speed,and solved the contradiction between the convergence speed and precision.The identification strategy is applied to the back EMF observer model to ensure the accuracy of rotor position observation.Then,the rotor position observation error suppression strategy based on complex coefficient adaptive observer(CCAO)is studied.The influence of dead time and sampling error on motor control is discussed.And the process of harmonics in position is explained by mathematical model.Because the traditional PI type extended back EMF observer has the characteristics of low pass filter,the rotor position observation method based on this observer is difficult to determine the appropriate parameters to suppress harmonics while ensuring the dynamic performance of the system,and cannot restrain DC bias.In this paper,the CCAO is used to replace PI type extension back EMF observer.The designed observer has simple structure and no complicated parameter setting.It can not only track the fundamental frequency signal without amplitude deviation and phase deviation,but also filter out the high harmonic and DC disturbance well,so as to suppress the rotor observation error.Finally,to verify the accuracy and effectiveness of the above methods,the proposed rotor position error suppression strategy based on parameter identification is simulated and verified by Matlab/Simulink and dSPACE hardware-in-loop simulation platform of 1.5k W interior PMSM.The results show that the proposed method can not only solve the rotor position error caused by parameter mismatch,but also suppress the rotor position pulsation caused by inverter dead zone effect and sampling error,which improve the PMSM sensorless control reliability of the motor.