Research On Parameter Identification And Sensorless Strategy Of Permanent Magnet Synchronous Motor

Permanent magnet synchronous motor(PMSM)has merits of simple structure design,good control performance,wide speed range.In addition,permanent magnet synchronous motor has been widely applied in intelligent manufacturing,industrial automation and other high-performance servo control field along with reduction of material costs,as well as the continuous improvement of PMSM control technology and the rapid development of DSP and other microprocessors.However,permanent magnet synchronous motor is a nonlinear system with high-order coupling and its parameters of motor stator resistance and inductance are easily influenced by temperature rising,flux saturation and other factors,leading to the decline of motor reliability and control performance.On the other hand,the accurate rotor position and speed information is the key to realize high performance control of PMSM.The traditional method is to install the mechanical sensor to obtain information,which actually restricts the application of permanent magnet synchronous motor due to cost and maintenance factors.Therefore,parameter identification and sensorless control has become a hot topic in the field of Motor Research.The main work is as follows:Firstly,the PMSM mathematic model of permanent magnet synchronous motor is given,and some methods of parameter identification and sensorless control are compared.Then briefly show the vector control technique,selects the decoupling method of id =0 and analyzes the effects of electrical parameters on the system decoupling,speed estimation and motor control performance to further indicate the importance of parameter identification.Secondly,in order to overcome the shortages of teaching-learning-based optimization algorithm such as converges slowly and easily gets stuck on local solutions in solving complex optimization problems,an improved teaching-learning-based optimization algorithm was proposed to identify the permanent magnet synchronous motor parameters.In the teaching phrase,tutorial teaching mechanism was introduced to strengthen teacher’s capacity and improves the convergence rate of algorithm,in the learning phrase,the course stepwise learning was used to improve learners’ learning efficiency.Besides,opposition-based-learning was introduced for small probability mutation,which enhanced the possibility out of local optima.The validity of the above analysis is verified by testing the performance of the benchmark function.The simulation result shows that the proposed algorithm can effectively identify the PMSM electrical parameters and have good convergence and reliability.Finally,considering the chattering phenomenon of the sliding mode,the chattering mechanism of the sliding mode control is demonstrated from the mathematical point of view,Based on the mathematical model of PMSM two-phase stationary coordinate system,an improved sliding mode observer is designed to observing rotor position and speed,which introduces the segmented hyperbolic tangent function as the switching function and the variable sliding mode gain to weaken the chattering.And considering the problem of parameter change in the actual operation of the motor,the observer conducts on-line identification for the stator resistance and gives feedback to the observer to further improve the observation accuracy.Then adopts fractional order phase-locked loop to estimate the rotor position and speed to effectively avoid the computational complexity caused by the traditional phase compensation.The effectiveness of the improved sliding mode observer is verified by experiments on the speed and position in MATLAB/Simulink under different conditions.