Research On Multi-objective Optimization And Longitudinal Following Control Of Intelligent Electric Vehicles

With the continuous development of urban traffic intelligence,the electrification,intelligence,networking and sharing of automobiles have become the hotspots of automotive industry research.Longitudinal dynamic control is one of the key links to realize the intelligent of electric vehicles.It determines the basic performances such as safety,economy and comfort of the car.However,for the longitudinal follow-up control of the bicycle,it is only from a single performance.It is difficult to achieve comprehensive optimization of multi-performance targets.Research on distributed electric vehicle longitudinal following control algorithm based on multi-performance target synergy has certain theoretical value and practical significance for improving intelligent vehicle anthropomorphic driving and its comprehensive performance.This paper combines some research contents of the national key R&D project “Study on the key basic issues of sensing,decision-making and control of intelligent electric vehicles”(2016YFB0100905)to study the quantification of multi-target performances such as safety,economy and comfort of distributed electric vehicles.Methods,the hybrid multi-performance target optimization cost function and constraints are established.The model multi-objective cooperative optimization longitudinal follow-up control algorithm based on Model Predictive Control(MPC)is proposed to improve the comprehensive performance of distributed electric vehicle longitudinal intelligent control,the main research work of this paper is as follows:(1)Modeling of vehicle dynamics in distributed electric vehicles.According to the structure and working principle of distributed electric vehicles,the dynamic model of distributed electric vehicle powertrain is established by Matlab/Simulink software.Based on the standard vehicle model in CarSim,the dynamics of distributed electric vehicle CarSim/Simulink is constructed.Model and verify its accuracy.(2)Collaborative optimization of multi-performance targets for distributed electric vehicles.Based on the theory of vehicle longitudinal kinematics,this paper studies the multi-objective performance quantification methods of safety,economy and comfort of distributed electric vehicles,establishes the hybrid multi-performance target optimization cost function and constraints,and uses the model prediction rolling optimization theory to multi-mix.Performance objectives are optimized to obtain longitudinal follow-up desired acceleration based on coordinated optimization of vehicle multi-performance targets.(3)Research on longitudinal tracking control of distributed electric gas vehicles.Based on the longitudinal acceleration of the vehicle with multiple performance targets,the fuzzy PID control theory is used to coordinate the control of the distributed electric vehicle drive motor.The established multi-objective optimization based longitudinal follow-up system is validated and selected to be linear twice.The optimal control for the upper layer is compared with the vertical follow-up system of the upper layer,and the four modes of the previous car lane change,the front car change lane departure,the front vehicle acceleration,and the front vehicle emergency brake are used to perform off-line simulation of the vehicle longitudinal tracking control strategy.Analysis to improve the overall performance of vehicle longitudinal intelligent control.