Online Parameter Identification Of Low Velocity And Huge Torque Permanent Magnet Synchronous Motor

Permanent magnet synchronous motor (PMSM) has been widely used amongdifferent industrial fields for its many advantages such as its small size, reliableoperation and high efficiency, etc. For the high precise control of permanent magnetsynchronous motor speed control system, the motor parameters affect more of theperformance of the control system. In most cases, the motor parameters used by thecontrol system are usually the offline parameters of the motor. As the motorparameters changes with the change of motor temperatures, the magnetic saturation,motor aging and other factors, therefore, the initial parameters of motor will not beable to effectively improve the control performance of the system. As a result, moreand more research scholars pay attention to the online parameter identification ofpermanent magnet synchronous motor.This essay starts from the analysis of the mathematical model of the permanentmagnet synchronous motor, analyses the influence of the motor parameters on theperformance of the controller, summarizes the more important parameters ofpermanent magnet synchronous motor in the vector control strategy. For thedegeneration of motor parameters when the system is online, the online identificationmethods of the inductance and the stator resistance of permanent magnetsynchronous motor based on the model reference adaptive are introduced in this paper.by using the Lypunov Stability Theory combined with the α-β axis mathematicalmodel of the motor, the adaptive convergence law of the to-be identified parameters isdeduced, the online parameter identifications of the inductance, stator resistance areachieved, and the effectiveness of the identification algorithm and the parametertracking performance is verified through the simulation. On this basis, this essayanalyses the influence of the rotor flux on the stator resistance identification, and thecoupling relationship of the rotor flux and stator resistance identification is gained. Asto that coupling relationship, this essay further puts forward a multi-parameter on-linedecoupling identification method which can simultaneously on-line identified theinductance, the stator resistance and the rotor flux. By using the negative sequenced-axis current injection method combined with the neural network onlineidentification strategies, utilizing the changes of the d-axis voltage, the decoupling identification of the stator resistance and rotor flux is achieved. The simulation andthe experience verified the validity of the decoupling identification algorithm.Taking advantage of digital control structure jointly by DSP and FPGA, apermanent magnet synchronous motor vector control experimental system featuresgood steady-state response and stable performance has been established. And thepermanent magnet synchronous motor (PMSM)’s online parameter decouplingidentification experiment is completed which further provide a more reliableexperimental proof for the theoretical analysis in this essay.