Research On Model Predictive Control Strategy Of Hybrid Electric Vehicle Platoon In Intelligent Networking Environment

Facing the resource shortage and environmental pollution crisis on the earth,energy-saving,safe,comfortable and environmentally friendly vehicles is the current development goal of the automotive industry.The emergence of intelligent connected cars provides new ideas for solving environmental and energy problems.This article takes the intelligent networked hybrid electric vehicle(HEV)fleet as the research object with the urban road environment as the background,and aims to improve the fuel economy,comfort and safety of the entire fleet.Model predictive control(MPC)is applied to this paper and a hierarchical control architecture is designed for the research method.The main research work of the full text are as follows:(1)The hierarchical control framework of the intelligent connected the HEV platoon is built based on MPC;the quasi-static mathematical model of the main dynamic components of hybrid vehicles: engine,motor,generator,and battery are built based on MATLAB software;and longitudinal dynamic model of automobile system is built.(2)The optimal speed design of the HEV fleet based on MPC in upper layer.Establish the optimization function of the stability and fuel economy of the plant;establish the fuel consumption model and the multi-car following model;plan the range of target speed based on the obtained traffic lights information on the road;explain the principle of model predictive control;design the model predictive control algorithm and optimize the vehicle velocity,the number of accelerations and decelerations,the following distance between the front and rear cars,and fuel consumption.(3)Research on energy management strategy based on MPC in lower layer.Explain the basic concepts of energy management,define an objective function to improve fuel economy and the variety of SOC,perform energy management of HEV based on the MPC algorithm,and optimally distribute the power between the engine and the battery;explain the principle of the dynamic programming algorithm;The global optimal energy management of HEV is implemented based on dynamic programming(DP);the simulation results of MPC and DP optimization are compared and analyzed.