Research Of Speed Sensorless Vector Control System Based On Stator Flux-oriented

The fast development of power electronics,micro-electronics and modern control theory brought huge impulsively effects to the development of the advanced control strategies for asynchronous motor. For the theoretical study, this paper takes the sensorless vector controlled system of asynchronous motor as the main research object. Around the pivotal technologies such as stator flux estimation, speed sensorless and on-line estimating of stator resistance et al, This paper carried deeply researches from the theory analysis,computer simulation et al. The simulation results confirmed the correctness of theoretical analysis.The flux estimation is the most important question in speed sensorless control. Less parameter in stator flux estimation are required than in rotor flux estimation. So the speed sensorless vector control of IM based on SFO is more robustness to parameters than it based on rotor flux orientation (RFO). In this dissertation, the start point and principle of the SFO have been represented in detail, the decoupling methods between flux and torque have been profound discussed, the control structure of the speed sensorless vector control based on SFO has been constructed, and the influences on the system performance by the inductances are also analyzed theoretically.In stator flux estimation, the saturation and DC drift will be easily produced by the pure integrator. The previous questions can be silenced by the one-order low pass filter (LPF), but the errors in magnitude and phase angle will be introduced inevitably. In this dissertation, the profound research on the theory, characteristic of the integrator with feedback compensation and the principle of parameter selection has been made. The limiting level fixed dual integrator can silence the saturation and DC drift questions, and can compensate completely the errors in magnitude and phase angle under the low frequency and saturation condition. The well stator flux observation result has been achieved by applying the limiting level fixed dual integrator to the stator flux observation.Speed identification is a pivotal technology to speed sensorless system. This dissertation presented a detailed derivation and gave a specific speed identification algorithm.The parameters of IM will vary with the change of operating condition. The stator flux estimation nearly correlates with stator resistance in the speed sensorless system based on SFO. In this dissertation, a close loop on-line estimating method of stator resistance is presented. This method is easily realized and its theory is simple. The simulation results show that the stator resistance variation can be well traced and the system performance is improved by using this method.