Research On Sensorless Control And Parameter Identification Of Permanent Magnet Synchronous Motor

In recent years,with the development of material technology and the improvement of permanent magnet material performance,permanent magnet motor has become the representative of high power density and high efficiency motor.In addition,compared with the traditional electron excitation synchronous motor,permanent magnet synchronous motor(PMSM)also has the advantages of simple structure,reliable operation,small volume,light weight,low loss and so on.Therefore,PMSM is widely used in civil use,aerospace,military and other fields.However,permanent magnet synchronous motor is a complex object with multivariable,strong coupling,nonlinear and variable parameters.In order to achieve good control performance,it is meaningful and necessary to study the control strategy of PMSM.Firstly,the paper introduces the research background and present situation of PMSM control strategy.The structure and working principle of permanent magnet synchronous motor are introduced.Besides,the characteristics,working mode and theoretical basis of vector control are analyzed.On this basis,the principle and realization of space vector width modulation are studied in detail.Secondly,an Elman Neural Network(ENN)based observer is proposed for the sensorless control of the Permanent Magnet Synchronous Motor.The ENN,which captures the dynamic behavior of a system,requires fewer neurons and converges precisely.A novel online training strategy is formulated based on the characteristics of ENN training and the sensorless control of PMSM,which can realize the adaptation of the ENN based observer and the precise estimation of speed and position of PMSM.The stability of the ENN training process is analyzed using the Lyapunov stability theory.The performance of the ENN based observer is analysed under various factors such as mechanical parameter variations,load disturbance,electromagnetic parameter variations,which can influence the sensorless control performance of PMSM.As the simulation results demonstrate,the ENN based observer presented in this paper is highly robust and precise.Lastly,A multi-parameter online identification method based on full rank identification equation for interior permanent magnet synchronous motors is proposed.By taking sample of two sets of quadrature axis and direct axis current,quadrature axis and direct axis voltage,electrical angular velocity signals,and substituting them into discrete voltage equation,the full rank identification equation is constructed,whicheffectively solves the problem of rank-deficient and realizes simultaneous online identification of stator resistance,quadrature axis inductance,direct axis inductance,and permanent magnet flux.This identification method does not rely on any design value of electromagnetic parameters and does not need to inject special disturbance signal.The Levenberg-Marquardt algorithm is used to solve the identification equation,and the iterative speed and solving precision can be improved effectively by updating the damping factor adaptively.In addition,the stability of electromagnetic parameters identification process is analyzed by Lyapunov stability theory.The simulation results show that the proposed identification method can realize multi-parameter simultaneous online identification,identify the parameters quickly and accurately,track the parameters mutation and slow change.Moreover,this identification method is always effective,regardless of whether the motor is running in transient or steady state.