Online Identification Of Electrical Parameters And Its Applications For Pmsms Based On Average Model/Switching Model

Permanent magnet synchronous motors(PMSMs)are widely used in the most fields such as servo system and electrical vehicles,for their high efficiency and high power density.PMSMs are often required a good control performance,and online identification of electrical parameters is crucial for performance improvement especially when the parameters are varying;In addition,some electrical parameters are significant indicators for the condition monitoring,i.e.,PM flux linkage can be used for early diagnosis of demagnetization fault.The electrical parameters of PMSMs mainly include stator resistance,d/q-axis inductance and PM flux linkage,etc.However,the voltage equations in the common PMSMs model are not sufficient to identify all of four electrical parameters during steady-state operation,which is also called rank-deficient problem.This problem will lead to the ill-convergence of all electrical parameters awaiting to be identified,limiting the application of parameter identification.In view of the above problems and difficulties,this paper conducts a series of researches on the online identification methods of electrical parameters for PMSMs,and the application of electrical parameters identification in motor control and condition monitoring.Firstly,the current research status of the electrical parameter identification methods and their applications for PMSMs is reviewed,the impact of rank-deficient problem is clarified and the main solutions are summarized.Based on the average model of IPMSM,the electrical parameters identifiability is analyzed and the cause of the rank-deficient problem are derived mathematically.Two methods to solve the rank-deficient problem under the average model are investigated in depth:two-separation identification based onαβcoordinate is proposed and it is proven that one voltage equation in theαβcoordinate can be used to identify two parameters;identification based on globally-time-varying signal injection is proposed,compared with the locally-constant signal injection,the convergence rate of parameters has been improved.Secondly,the IPMSM switching model is built from SVPWM,and the relationship between switching and average model is revealed by the switching cycle average operator and the current sampling method.The identifiability under switching model is analyzed and it is proved that there exists no rank-deficient problem.Then the online identification of full electrical parameters for IPMSM based on switching model is proposed,which can be applied under the condition of"no signal injection and arbitrary initial values".Moreover,considering rotor position error,an improved inductance identification for IPMSM is designed without rotor position information.Based on theαβ-axis voltage equation in switching model,the rotor position angleθ_e is eliminated and the influence of rotor position error on the inductance identification is reduced.Then,the online IPMSM electrical parameters identification based on switching model is extended to SPMSM,the identifiability is analyzed and the mechanism of rank deficiency under i_d=0 control is explained.To solve this problem,three schemes have been proposed based on switching model:(1)ignoring resistance under high-speed conditions,with which the impact of rotor position error is removed;(2)constant i_d≠0 control,with which the stator resistance,inductance and PM flux linkage could be identified simultaneously and no speed variation will be produced;(3)adopting second-order current derivative.The pros and cons of these three schemes are given.Finally,the application of the switching model-based identification of electrical parameters of PMSM is investigated,such as motor control performance improvement(e.g.,online MTPA correction)and health/operation condition monitoring(e.g.,assisted diagnosis of demagnetization fault).For the problem of MTPA curve deviation due to IPMSM parameter mismatch,based on the IPMSM switching model,the difference between d/q-axis inductance and PM flux linkage are estimated for the online MTPA correction.On the other hand,to assist in the diagnosis of uneven demagnetization fault for SPMSM,the impact of slot-pole combination is analyzed.For the motors without fault-related harmonics,the parameter identification method is used to estimate the PM flux linkage to detect the fault.While for the motors with fault-related harmonics,a method based on motor current derivative analysis(MCDA)is proposed,compared with the conventional motor current signal analysis(MCSA),the qualitative and quantitative discrimination ability are summarized when the load is balanced and unbalanced.In this thesis,the proposed online identification method of electrical parameters and its application are verified in details through simulations and experiments,in the end,the main work and contributions of this thesis are concluded,and the outlook of future research is presented.