基于IDP的重型商用车自适应距离域预见性巡航控制策略  

An IDP-Based Adaptive Range-Domain Predictive Cruise Control Strategy of Intelligent Connected Heavy-Duty Commercial Vehicles

作　　者：李兴坤[1,2] 王国晖 卢紫旺 王玉海 王语风 田光宇[1] Li Xingkun;Wang Guohui;Lu Ziwang;Wang Yuhai;Wang Yufeng;Tian Guangyu(Tsinghua University,State Key Laboratory of Automotive Safety and Energy,Beijing 100084;Beijing Yujun Automotive Technology Research Institute Co.,Ltd.,Beijing 100020;Qingdao Yu Le Intelligent Technology Co.,Ltd.,Qingdao 266000;Faw Jiefang Qingdao Automobile Co.,Ltd.,Qingdao 266000)

机构地区：[1]清华大学,汽车安全与节能国家重点实验室,北京100084 [2]北京裕峻汽车技术研究院有限公司,北京100020 [3]青岛驭乐智能科技有限公司,青岛266000 [4]一汽解放青岛汽车有限公司,青岛266000

出　　处：《汽车工程》2024年第8期1346-1356,共11页Automotive Engineering

基　　金：国家自然科学基金(52272372)资助。

摘　　要：为降低重型商用车燃油消耗、减少运输成本,本文协调“人-车-路”交互体系,将车辆与智能网联环境下的多维度信息进行融合,提出了一种基于迭代动态规划(iterative dynamic programming,IDP)的自适应距离域预见性巡航控制策略(adaptive range predictive cruise control strategy,ARPCC)。首先结合车辆状态与前方环境多维度信息,基于车辆纵向动力学建立自适应距离域模型对路网重构,简化网格数量并利用IDP求取全局最优速度序列。其次,在全局最优速度序列的基础上,求取自适应距离域内的分段最优速度序列,实现车辆控制状态的快速求解。最后,利用Matlab/Simulink进行验证。结果表明,通过多次迭代缩小网格,该算法有效提高了计算效率和车辆燃油经济性。In order to reduce fuel consumption and transportation cost of heavy-duty truck,this paper coordinates the human-vehicle-road interaction system,integrates multi-dimensional information of vehicles and intelligent network environment,and proposes an adaptive range-domain predictive cruise control strategy(ARPCC)based on iterative dynamic programming(IDP).Firstly,by combining the vehicle status and multi-dimensional information of the front environment,an adaptive distance domain model is established based on the longitudinal dynamics of the vehicle to reconstruct the road network,simplify the number of grids,and obtain the global optimal speed sequence by IDP.Secondly,on the basis of the global optimal speed sequence,the segmented optimal speed sequence taken from the adaptive distance domain is obtained to realize the fast solution of vehicle control state.Finally,Matlab/Simulink is used to verify the results,and the results show that the algorithm can effectively improve the computational efficiency and vehicle fuel economy by reducing the grid several times.

关 键 词：重型商用车 自适应距离域 预见性巡航 迭代动态规划 

分 类 号：U463.6[机械工程—车辆工程]