Model Predictive Control Of Switched Reluctance BSG Motor For Hybrid Electric Vehicles

With the increasingly serious problems of environmental pollution and resource shortage,more and more attention has been paid to energy conservation and emission reduction.The electric vehicle is one of the important measures of energy saving and emission reduction.Recently,as the transition of pure electric vehicle,hybrid electric vehicle is very popular.Among them,the belt driven starter generator(BSG)micro hybrid system is the research hotspot of hybrid technology.Compared with other types of BSG motors,SRM has many advantages,such as without permanent magnet,simple structure,large starting torque and so on.This project comes from the key project of National Natural Science Foundation of China(U1564201)and the outstanding youth project of Jiangsu Province(BK20180046).In this paper,nonlinear modeling,model predictive control,rapid control prototype platform based on dSPACE and experimental verification of fault-tolerant 16/10 pole segment rotors switched reluctance motor(SRSRM)for hybrid electric vehicle are studied.The main dissertation contents are as follows:1)On the basis of expounding the structure of new fault-tolerant 16 / 10 pole SRSRM motor,the operation principle of SRSRM is introduced.According to the principle of electromechanical energy conversion,the electromechanical conversion relationship of SRSRM is described by circuit equation,mechanical equation and electromechanical equation.Three kinds of SRSRM mathematical models are compared.Considering the precise motor control,the nonlinear model is selected as the mathematical model.Finally,the operation mode of SRSRM is analyzed.2)In order to establish the SRSRM nonlinear model,through the torque balance method,the current and voltage values at the specific position where the static torque is zero are collected,and then the flux value of the position is calculated.The second-order and fourth-order Fourier series flux model and torque model are established.By comparing the modeling results,the more accurate fourth-order Fourier series is selected to build the model.However,Fourier series can only express the relationship between rotor position angle and flux linkage.To solve this problem,Kriging model is introduced to further optimize the nonlinear model.On this basis,the Simulink motor model is built for simulation verification.3)In view of the shortcomings of traditional control methods of SRSRM,the control strategy of model predictive control is proposed to suppress the torque ripple of SRSRM.Based on Kriging flux model,a model predictive current control model is built,including mathematical model and cost function.In order to solve the problem that it is difficult to collect the real-time flux through the sensor,a Kalman flux observer is established.In view of the shortcomings of the traditional PID control,the auto disturbance rejection control is introduced as the speed loop controller.In addition to indirectly restraining the torque ripple through the current,directly restraining the ripple through the torque is also a control method.Based on a nonlinear torque model,the model predictive torque control model is established,and the vector selection and cost function establishment are introduced.In order to further restrain the torque ripple of SRSRM,the torque distribution function is introduced.Based on the two models,the simulation analysis is carried out.4)Based on dSPACE controller,the rapid control prototype development platform is designed.The hardware design steps are introduced in detail,including: drive circuit,protection circuit,sensor circuit,etc.the selection of software interface is introduced.Finally,a rapid control prototype development platform is built preliminarily,which lays a foundation for SRSRM experimental research.5)Based on the SRSRM rapid control prototype development platform,the SRSRM experiment platform is constructed,and relevant experiments are carried out,including torque balance method,nonlinear model and model predictive control algorithm.The experimental results verify the correctness of the theory and simulation.