Intelligent driver model based optimal control for energy efficiency of electric vehicle
LU Li-qun
ZHANG Jiang-yan
ZHANG Tao
Abstract：Related research shows that optimal control strategies that involve the future power demand prediction could improve the vehicle energy efficiency significantly.On the other hand,the intelligent driver model(IDM)provides an algo-rithm that can provide a quantitative predictions of future vehicle states with the data obtained by using connected vehicle technologies.This paper proposes an improved IDM to predict the vehicle states with high accuracy,using this prediction algorithm,a model predictive control(MPC)formulation is proposed to deal with the energy management issue of electric vehicles.The energy consumption is taken as the objective function,and in order to further expand the optimization space,a car-following model with fixed headway is improved by introducing the relaxation processing mechanism.The study shows that the solution of the proposed problem guarantees the energy conservation and safety,and further improves the traffic efficiency.Finally,an evaluation platform is constructed by using multi-mode traffic scenario simulation software SUMO and MATLAB software.The validation results show that the proposed MPC strategy can not only improve the traffic efficiency,but also improve the energy efficiency by 5.05％,3.2％and 4.15％,respectively with respect to three signalized intersections road operating scenarios.
Keywords：electric vehicleintelligent driver modeldriving style recognitionenergy efficiencymodel predictive control
Publication Date：2025-08-30
Online Publishing Date：2025-10-10(First online date of this platform, not the publication date of the document)
Pages：10( 1543-1552 )