Research On Improvement Of Position Sensorless Control Algorithm And Motor Efficiency Optimization Of HPMSM

High-speed permanent magnet synchronous motor(HPMSM)are important power sources for transmission systems such as high-speed motorized spindles,vacuum molecular pumps,centrifugal compressors,due to their high-power density,small size,simple structure.High performance control of HPMSM requires accurate rotor position information,and stable efficiently driving is essential to achieve excellent performance of HPMSM.To explore the HPMSM high efficiency non-inductive vector control algorithm,a high-speed centrifugal compressor HPMSM is studied from aspects of motor position observation and efficiency optimization,The main research work and contents are as follows:A new position sensorless control method is proposed,based on the speed observer of the improved current estimation model,which can realize the speed observation in the full speed domain with a single control algorithm.The problems of the extended back-EMF speed estimation method such as unstable state switching,limited application range and poor start-up performance are solved.A new estimated rotational coordinate system is established,and the error between estimated current value and the actual current value is used as the input of the speed observer,besides the observer parameters selection principle is given.The initial speed is estimated,and quadrature axis current error is used to correct the initial speed to obtain the final estimated speed.The motor can be directly started with the closed-loop vector from the static state,and there is no state switching problem from low speed to high speed.Moreover,load capacity,dynamic performance,and robustness are improved by the method.Optimal control method for medium and low speed PMSM is studied.The id=0control and unity power factor control are compared by theory and simulation methods,which found the id=0 control method is more efficient for medium and low speed PMSM.Efficiency optimization control of HPMSM is studied.Motor iron loss is considered to reconstruct the PMSM mathematical model,the controllable electrical loss expression is derived,and the objective function is established.The direct-axis current under the optimal efficiency is solved,and the efficiency optimization control is achieved.To solve the problem of efficiency optimization robustness,an efficiency optimization control method based on search model is proposed from the perspective of system power.In constant motor power situation,the minimum input power is continuously searched to realize the efficiency optimization control.To settle the conflict between search time and search accuracy,a set of fuzzy control rules for the surface mounted PMSM is designed,hence the minimum input power is adaptively searched with variable step size,which is independent of motor parameters,and the PMSM efficiency optimization control is realized.The adaptive variable step efficiency search control algorithm and the sensorless vector control algorithm simulation model based on the improved current model are built on the Matlab/Simulink software platform.The simulation results show that the adaptive variable step efficiency search control algorithm can quickly find the minimum input power and achieve efficiency optimization control.The proposed sensorless vector algorithm can realize full domain speed estimation with a single algorithm,while dynamic response and robustness are improved.A motor test rig is built,and the proposed algorithms are verified by experiments.