| This paper mainly takes the built-in permanent magnet synchronous motor as the research object.When the motor works,it needs to use a variety of sensors,such as voltage,current,position and temperature sensors.Due to the constraints of realistic conditions,it is often not convenient to install corresponding sensors.Using a specific algorithm to realize the function of sensors has gradually become the focus of modern motor control research.In this paper,in view of the sensorless control technology are studied,considering the motor in the actual work,its internal parameters are influenced by temperature,which affect the estimate precision of sensorless control algorithm,so the average temperature of the motor to estimate for the inquiry,and then based on the temperature properties of the metal resistance estimation of stator resistance under different working conditions.Finally,because the motor is adopted in different speed when the domain is different sensorless control algorithm,in order to make the motor at full speed range to achieve sensorless control,USES a composite control method based on particle swarm optimization algorithm optimized combined two kinds of control algorithm,and the method with the traditional method of hysteresis switching and weighted switching method to estimate the error were analyzed.The main research contents of this paper are as follows:First of all,according to the mathematical model of permanent magnet synchronous motor vector control and SVPWM algorithm to build the vector control of permanent magnet synchronous motor speed control system,in order to reduce the motor loss and broaden the motor speed range,the maximum torque current ratio(MTPA)and weak magnetic control strategy for the introduction of permanent magnet synchronous motor vector control system,when the motor speed is less than the base rate,The maximum torque current ratio control strategy is adopted.When the motor speed is greater than the base speed,the magnetic weakening control strategy is adopted.The simulation model of vector control system with position sensor based on MTPA+ magnetic weakening is built.Secondly,on the basis of MTPA+ weak magnetic control strategy,the sensorless control technology of the motor is studied.When the motor is at low speed and medium high speed,the rotor position information is estimated by using pulse high frequency voltage injection method and model reference method,and then the error analysis of the two estimation methods is carried out.It mainly includes constant torque variable speed condition and constant speed variable torque condition.According to the simulation results,the accuracy of the two estimation methods is good,and both of them can meet the working requirements.Then,due to the motor stator resistance change is mainly affected by temperature is bigger,so this paper proposes a motor as a stable equivalent heating element,the motor of various losses as a heat source,and considering the motor heat dissipation structure,and heating of the motor is set up respectively in the Simulink model and thermal model,According to energy conservation law and heat dissipation formula,the average temperature of motor under different working conditions is estimated.Then,the finite element model of the heat dissipation structure of the motor is built in the THREE-DIMENSIONAL software,and the temperature of the motor is calculated,and the two different estimation methods are compared and analyzed.Finally,based on the temperature characteristics of metal resistance,the stator resistance value of the motor under different working conditions is estimated.Finally,in order to achieve sensorless control motor at full speed range,with composite control method will be applied to low speed pulse vibration in high frequency injection method and is suitable for high speed model reference adaptive combined,realize the complementary advantages,considering two different estimation error is different,then establish a minimum speed estimation error variance as the fitness function,The particle swarm optimization algorithm is used to optimize the weight coefficient of the weighting function,and then it is compared with the traditional hysteresis switching method and the weighted average switching method.According to the simulation results,the optimized switching algorithm can make the motor switch more smoothly in the transition region. |
