Parameter Estimation Of Ipmsm Based On Affine Projection Algorithm

Interior permanent magnet synchronous motor(IPMSM)has been used in an increasing number of application domains,such as home appliances,industrial control,electric vehicles and so on,due to its advantages of high efficiency,high power factor and good dynamic performance.As for the vector control system for IPMSM,the design of controllers is very important whose accuracy is usually affected by the parameters of IPMSM.However,such parameters always change during system operation.For example,the stator resistance and rotor flux linkage of IPMSM always change with the variation of the motor temperature,while the stator inductances of IPMSM are always determined by the saturation level of the iron core.In order to obtain such information,it is very important to estimate parameters of IPMSM online.Meanwhile,under some operation state,conventional parameter estimation method can make the identified results fluctuated or even not convergent.Therefore,this thesis mainly focuses on the parameter estimation based on self-adaptive stepsize affine projection and the estimation method based on square-current injection.In this paper,based on the development analysis of IPMSM parameter online estimation technology,space vector control technology,the mathematical model of IPMSM is established.According to the characteristics of the parameter estimation equation matrix,the necessity and superiority of the parameter estimation based on self-adaptive stepsize affine projection and the estimation method based on square-current injection have been demonstrated.Parameter estimation based self-adaptive stepsize affine projection is proposed to solve the problem of bad convergence of parameter identification algorithm.The stepsize choosing guideline is added to overcome divergence of estimated parameters after motor operation condition change and can make sure that the output of identification algorithm reaches an accurate result.By using speed and current signals of motor to calculate the stepsize of algorithm,the risk of manual choosing that value can be eliminated,which can improve the stability of parameter estimation.Additionally,the stability analysis is carried out and the stepsize selection is illustrated.In order to further improve the accuracy of parameter estimation,a parameter identification method based on square-current injection is proposed.Based on analysis of the effect of given parameters and inverter nonlinearity on the parameter online estimation,the necessity of signal injection and the form of injected signal are discussed.The error analysis of the proposed parameter identification method is presented.And the range of choosing the magnitude of injected current signal is illustrated.Finally,the proposed parameter online estimation strategies are validated on both Matlab/Simulink simulation platform and the 2.2k W permanent magnet synchronous machine drive test platform.Under changing load and changing speed conditions,the experimental comparisons between the parameter estimation based on conventional affine projection and the method based on self-adaptive stepsize affine projection are carried out,respectively.The experimental results validates that the proposed parameter online estimation method.Meanwhile,the improvement of parameter estimation accuracy of proposed strategy is validated by the experimental comparisons between the method with and without square-current signal injection.According to experimental results,contrastive analysis of the two proposed methods has been illustrated.