Research On Closed Loop Identification System For Nonlinear And Harmonic Parameters Of Permament Magnet Synchromous Motor

As energy transfer and executive components, motors are important components of the electric driven system, which is the main driving method for machinery and equipment. Because of the high reliability, high torque inertia ratio and the good effect of energy-saving, the permanent magnet synchronous motor is widely used in advanced and traditional industry fields. However, the dynamic and steady control performance is reduced for the nonlinearity and harmonic of the motor parameters. So far by now, only rely on improving the control method, the influence which caused by the nonlinearity and harmonic of motor parameters can't be completely eliminated. The parameter identification could get the real-time parameters base on the input and output data of motors. It's an effective way to avoid the influence of the nonlinear and harmonic of the motor parameters and also to improve the control performance. In this paper, based on the nonlinear and harmonic parameters identification model of permanent magnet synchronous motor, the influence of the closed-loop identification system error on the parameter identification is analyzed and suppressed, the closed-loop identification method of motor parameter is deeply studied, and then, the precise parameter identification and the dynamic quality of online parameter identification are realized, and the aim to improve the control quality is satisfied.To quantitatively analyze the influence of the error of closed-loop links on the motor parameter identification, the model of nonlinear and harmonic parameter identification of PMSM, which considering the feedback errors of the current sensors and the encoder, and the voltage output error of the inverter of closed-loop system, is established. And based on this model of the parameter identification, the influence rules of closed-loop links errors on the motor parameter identification is obtained when using the method of the offline steady-state parameter identification.Based on the analysis of the causes of the current feedback error of sensors, the angle error of encoder and voltage output error of the inverter, the delay error of the feedback current is eliminated by establishing the current state observer; the error and harmonic of the feedback angle is eliminated by proposing the electric re-correction method based on magnetic field position; Also dead-time compensation mathematical model of the half and full cycle current control is established, and the twin-stage current state observer is designed to predict zero crossing point of current, and then the dead time compensation method is improved. Through compensation and disposal to these key links of the closed-loop system, the foundation of the research on motor nonlinear parameters and harmonic value identification method is established. The model reference adaptive on-line identification method based on Popov stability theory is designed to identify the nonlinear parameters of motor, and the simulation platform to testify the results is built. In order to improve the dynamic quality of the parameters identification, the influences of the pole assignment of the linear forward path, parameters selection of the adaptive law and the input of the nonlinear feedback path on the astringency of parameters identification is analyzed, and the parameter regulated law which guarantee better dynamic quality of parameters identification is obtained. The proposed MRAS identification method based on feed forward make a further improvement on dynamic quality of online identification.The mathematical model of motor harmonics parameter identification is very complex and includes coupling harmonics of quantities of state, so the harmonics characteristic of the identification system state variables is analyzed, the identification model is simplified. Based on the theoretical analysis, through the measurement of the motor back-electromotive force harmonics and calculation, the harmonic amplitude of the permanent-magnet flux linkage is gained. In order to the self inductance harmonics and mutual inductance harmonics identified online, the state observer based on Liapunov theorem is designed, and the offline frequency spectrum analysis method is proposed to testify the online identification result.The closed-loop parameter identification system is developed, and the experiments to verify the suppression method of the closed-loop identification system error and the parameters identification method are implemented. Through the contrast of the results before and after compensation to the closed-loop system error, the validity of the compensation methods of the closed-loop system error is proved. Then the parameter regulation rules which improve the dynamic quality of the on-line identification method and the MARS method which is based on feed forward are verified. The comparison of the identification results of the self inductance and mutual inductance harmonics, which identified by using the Liapunov theorem-based state observer identification method and the off-line frequency spectrum identification method, show that the previous method gets agreeable result. And the harmonics of system state variables is reduced after injecting the identified harmonics to the control voltage. These results validate the proposed harmonics identification method. The analysis and test results above show that the proposed closed-loop identification system can realize the precise identification of the nonlinear and harmonic parameters of the motor, and build the foundation for the application of motor parameter dentification and the improvement of motor control.