Research On Sensorless Control Of PMSM For EPS

Electric Power Steering(EPS)system has the characteristics of speed assistance.when the vehicle speed is low,the assist motor can provide greater assistance,to ensure the portability of low speed steering;when the vehicle speed is high,the assist motor output small torque,to ensure the safety of driving.In addition,EPS can only provide power when steering,which can significantly reduce the fuel consumption of vehicles.Therefore,EPS has become the main direction of the development of automotive power steering system.Among them,Permanent Magnet Synchronous Motor(PMSM)has gradually replaced DC Motor as the main choice of EPS assisted Motor due to its high power factor,small size,large starting torque and gradually mature control technology.Accurate rotor speed and position signals are the basis of good control of PMSM.The traditional detection method is usually to install mechanical sensors(magnetic encoder,photoelectric encoder,solver,Hall position sensor or tachometer generator)on the rotor shaft to measure directly.However,the high resolution and high precision speed and position sensors have high cost and installation requirements,which increases the use and maintenance cost of PMSM,reduces the reliability of the system in extreme environments,limits the application and development of PMSM to a certain extent.In view of the above problems and the fact that EPS assist motor often works in low and medium speed,this paper mainly studies the low-speed sensorless control of PMSM for EPS as follows:(1)The research background of this topic and the research status of PMSM sensorless control strategy are introduced.In this paper,the current speed and position estimation algorithms of PMSM are summarized.Through comparative analysis,the high frequency injection method is selected as the research focus of sensorless control.(2)By comparing and analyzing the difference between space vector control and direct torque control,the control algorithm suitable for EPS PMSM system is obtained.The mathematical model of PMSM is derived and the transformation process of three coordinate systems is analyzed.The basic idea of vector control is expounded,the basic control principle and realization process of SVPWM technology are introduced in detail.On this basis,the corresponding simulation model is established.Through the analysis of the simulation results,it is concluded that the vector control PMSM is more suitable for EPS PMSM system.(3)The PMSM sensorless vector control system based on GaussCauchy hybrid mutation particle swarm optimization for PI parameters was established.In order to enhance the global and local searching ability of the algorithm,a nonlinear differential decrement inertia weight is proposed based on the traditional PSO algorithm.asynchronous time-varying learning factor is used to improve the convergence speed and accuracy.Secondly,the Cauchy-Gauss hybrid mutation strategy was introduced,which increased the diversity of the population and improved the problem that the algorithm is easy to fall into premature.Then,combined with the space vector control described above,the rotor speed and position of PMSM were estimated by high frequency injection method,and the PI control parameters of PMSM speed loop were optimized by Cauchy-Gauss hybrid mutation particle swarm optimization algorithm.The sensorless PMSM vector control system based on Gauss-Cauchy hybrid mutation particle swarm optimization algorithm for PI parameters was constructed.Finally,the corresponding simulation model is built to verify the proposed algorithm.The results show that the sensorless control strategy proposed in this paper can accurately track the speed and position of PMSM rotor,has good dynamic performance and anti-interference ability.(4)In view of the contradiction between speed response and disturbance rejection ability in the traditional PI controlled PMSM senseless control system,a compound control strategy combining the Diagonal Recurrent Neural Network(DRNN)with sliding mode control(SMC)and Higher order Romberg rotor position observer(HRO)was adopted.In order to improve the nonlinear approximation ability of the neural network,the bipolar flexible S function is used as the mapping function of DRNN recursive layer,which makes the parameters of the mapping function can be adjusted,and the nonlinear mapping ability of the system can be improved.The traditional d-axis current loop PI control is replaced by sliding mode control,and the hyperbolic tangent function is used to replace switching function to improve the control precision of the system.In order to solve the problem of large pulsation in the traditional PD form Romberg observer,the rotor position and speed were estimated by HRO.Simulation results show that the proposed DRNN-SMC-HRO sensorless composite control strategy can accurately track the rotor speed and position of PMSM at low speed,and has less speed ripple and steady state error.(5)According to the laboratory conditions,a motor test bench composed of the upper computer,the motor driving test box and the PMSM was built.Firstly,the motor experiment platform is built from both hardware and software,and then the two control algorithms proposed in this paper are compared with other algorithms.The experimental results are consistent with the simulation results,which further verifies that the control algorithm and control strategy proposed in this paper have higher estimation accuracy and anti-interference performance.