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Research On Speed Estimation And Parameter Identification Of Induction Motor

Posted on:2020-09-20Degree:MasterType:Thesis
Country:ChinaCandidate:X N LiFull Text:PDF
GTID:2392330599960513Subject:Engineering
Abstract/Summary:PDF Full Text Request
Induction motors are widely used in various control fields because of their low manufacturing cost,reliable operation and no demagnetization risk.Vector-controlled constant speed closed-loop algorithm can effectively improve the control performance of induction motor,but it needs to install speed encoder to get speed signal.This method increases the cost and reduces the reliability of the system.Therefore,the speed sensorless method of estimating speed by stator voltage,current signal and software algorithm becomes a practical scheme.Speed estimation algorithm in speed sensorless mode contains many motor parameters,the accuracy of speed estimation is closely related to the motor parameters,and motor parameters will be changed by external factors in the process of operation.Aiming at the above problems,this paper focuses on speed estimation and online parameter identification.The main work is as follows:Firstly,the model reference adaptive system(MRAS)algorithm based on rotor flux linkage is selected to estimate the speed.In view of the DC drift caused by the pure integration link of voltage model in the algorithm,the neuron adaptive integrator is used to replace the pure integrator,effectively eliminating the DC component contained in the voltage signal.Aiming at the problem that the current model is vulnerable to the misalignment of rotor time constant,a new MRAS speed estimation algorithm with rotor time constant identification is established,which eliminates the influence of rotor side parameter changes on speed estimation.The simulation and experimental results show that the proposed algorithm can effectively improve the speed estimation accuracy.Then,aiming at the problem that the voltage model is vulnerable to inaccurate changes of stator side parameters,the on-line stator side parameter identification is further studied.The cuckoo algorithm with fast optimization speed is selected to identify the stator inductance and resistance online.Tabu algorithm is combined to solve the problem that cuckoo algorithm is easy to fall into local optimum.Chaotic variable-scale local search algorithm is combined to solve the problem of poor local search ability of cuckoo algorithm.Because there is a steady-state under-rank phenomenon in multi-parameter simultaneous identification without speed sensor,a step-by-step identification method based on alternating stator-side parameter identification algorithm and MRAS speed estimation algorithm is proposed.Finally,the identified stator parameters are used to update the parameters of MRAS speed estimation algorithm,and the voltage model in the speed estimation module is modified in real time to eliminate the influence of stator parameters on speed estimation.The simulation results show that the cuckoo parameter identification algorithm can effectively identify the stator resistance and inductance.
Keywords/Search Tags:Vector control, Speed sensorless, Model reference adaptive system, On-line parameter identification, Cuckoo algorithm
PDF Full Text Request
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