The Research On Parameter Identification Of Synchronous Reluctance Motor Based On Magnetic Saturation Model

Compared with permanent magnet synchronous motors,synchronous reluctance motors have attracted increasing attention from scholars because of no permanent magnets and no rotor windings.The realization of high performance synchronous reluctance motor vector control strategy depends on the accuracy of the motor parameters,and the influence of temperature rise,magnetic saturation and other factors during the operation of the motor will lead to the disturbance of the parameters.Therefore,it is necessary to identify the parameters of the synchronous reluctance motor accurately and make the dynamic correction during the operation.The main work of this paper is to identify the resistance and inductance of the synchronous reluctance motor off-line and on line.Firstly,the mathematical model of the synchronous reluctance motor considering the magnetic saturation is analyzed.The current injection method is combined with the least squares method to identify the stator winding resistance and the stator winding inductance of the motor.The offline recognizing results are taken as initial values to carry out online parameter identification of synchronous reluctance machines which is based on recursive least squares method.The online recognizing parameters of synchronous reluctance machines based on recursive least squares method are deduced and verified by simulation.Secondly,the model reference adaptive method is used to identify the parameters of the synchronous reluctance motor online,and the model reference adaptive method based on the Popov adaptive law design is studied.The dynamic characteristics,such as identification speed,accuracy,and followability,are compared and analyzed when the model reference adaptive method and recursive least squares method are used for on-line parameter identification.An improved online identification algorithm for synchronous reluctance motor parameters is proposed for both characteristics.The improved algorithm sets the offline parameter identification result as the initial value of model reference adaptive.At the same time,the recursive least squares method with variable forgetting factor is introduced in the model reference adaptive method.The advantages of the two algorithms are combined.The simulation results show that the algorithm has the advantages of fast identification speed,high identification accuracy and good followability.Finally,a parameter identification system hardware experiment platform is built,and the proposed parameter identification system which based on the improved synchronous reluctance motor is verified in this paper.With Ti’s FAST position observer,sensorless parameter identification is achieved.The experimental data and simulation results show that the proposed synchronous reluctance motor parameter identification system can realize the parameter identification of the sensorless synchronous reluctance motor.Compared with the single identification algorithm,the proposed improved parameter identification algorithm is faster and more accurate than the single identification algorithm.