Research On Parameter Identification And State Observation For Induction Motor Drives

Motor drive system is the most important energy conversion method for modern industrial society.Along with industrialization and urbanization,electricity has a significantly increasing proportion in the final energy consumption,and more than half of total social electricity consumption is consumed for powering the motor,most of which provides three phase squirrel-cage induction motors.However,the motor drive and control system techniques of our country still lags far behind foreign countries result in lack of competitiveness in efficiency and other important indicators.With the rapid development of power electronics technology,chip technology and control theory,it is necessary to achieve a number of breakthroughs and upgrade the AC speed control technique,to satisfy the production and life demand,as well as the urgent demand for energy conservation.This dissertation focuses on parameter identification and high-performance control strategy of three phase squirrel-cage induction motor system.The parameter identification demands of different control strategies and operating conditions are firstly analyzed,followed by a thoughtful research on parameter identification and indirect field oriented vector control of induction motor.The main contents of this paper are:First,on the basis of mathematical modeling and analysis of induction motor,three schemes are described and analyzed.These schems have some characteristics in common:based on mathematical models,and achieving speed sensorless control with robust against stator resistance variation.A comparative analysis is proposed by firstly derive the adaptive law and error transfer function,and then draw the stability region based on the transfer function.According to the above above analysis,one of the three schemes,the parallel speed and stator resistance estimation based on rotor flux observation,has the advantages of global stability and low computation.The key issue of this scheme is how to overcome the problems caused by pure integrator.A new solution is proposed in the dissertation,which deduces the parallel speed and stator resistance adaptive law based on the derivative of rotor flux.The observer of derivative rotor flux is designed on the basis of super-twisting algorithm,which belongs to high order sliding mode theory.It successfully obtains good dynamic performance and alleviates the chattering behavior,as well as robust against variation of rotor resistance.Experimental results show the effectiveness and advantages of the proposed scheme.Second,according to observability analysis,speed and rotor time constant cannot be simultaneously observed when the amplitude of rotor flux is invariant.However,constant rotor flux is the precondition of steady operation.In this section,at the premise of known speed,online identification techniques and accurate authentication methods of rotor time constant are studied in the dissertation.Forgetting factor recursive least squares algortithm and adjusted particle swarm optimization algorithm are used respectively to achieve online identification of rotor time constant.In addition,experimental results verified that adjusted particle swarm optimization algorithm has better noise immunity than the other method.In the end,the negative impact of inaccurate rotor time constant on rotor field orientation is analyzed.Moreover,the phenomenon is utilized for accuracy verification and identification of rotor time constant.Finally,to achieve parallel speed and rotor time constant identification,the speed is estimated via rotor slot harmonic extraction technique,and adjusted particle swarm optimization method is utilized on the proposed simplified model to identify the rotor time constant.The existence condition of rotor slot harmonic and the relationship between speed and the frequency of rotor slot harmonics are discussed.Based on the analysis,a speed estimation scheme is proposed,which identifies the dominant rotor slot harmonic by motor type information,and estimates the speed via the specific relationship between the harmonic frequency and motor speed.Then a simplified derivative form of IM model is proposed for rotor time constant identification,and adjusted particle swarm optimization method is utilized on the proposed model to identify the value.The experimental results proved the effectiveness of the proposed scheme.