摘要
提出了一种新颖的车辆自适应巡航控制(ACC)系统,该系统可以在保障跟车距离的同时,提升车辆的燃油经济性。基于模型预测控制(MPC)进行ACC的上层控制器搭建,并在此基础上采用高斯过程回归(GPR),网格搜索(GS)和自适应方法进行三轨参数调整,将控制域和预测域调整到最优状态。此外,为了减少计算量并提高稳定性,系统采用了粒子群优化算法(PSO)对系统进行升级改进。仿真结果表明,基于MPC控制的车辆自适应巡航控制系统可以在保证良好跟踪性能的同时降低燃油消耗率。
A novel vehicle adaptive cruise control(ACC)system is proposed,which can guarantee the following distance and improve the fuel economy of the vehicle.Based on the model predictive control(MPC),the upper controller of ACC is built,and on this basis,the three track parameters are adjusted by using Gaussian process regression(GPR),grid search(GS)and adaptive methods to adjust the control domain and prediction domain to the optimal state.In addition,particle swarm optimization(PSO)are used to upgrade the system in order to reduce the amount of calculation and improve the stability.The simulation results show that the vehicle adaptive cruise control system based on MPC control can ensure good tracking performance and reduce fuel consumption at the same time.
作者
何臣修
郭世永
HE Chen-xiu;GUO Shi-yong(School of Mechanical and Automotive Engineering,Qingdao Technological University,Qingdao Shandong 266520,China)
出处
《机械设计与制造》
北大核心
2024年第2期30-35,共6页
Machinery Design & Manufacture
