多交叉口工况的网联汽车最优节油驾驶策略  被引量:7

Fuel-saving driving strategy for connected vehicles in multiple signalized intersections

在线阅读下载全文

作  者:辛喆[1] 余舟 郭强强 林庆峰[3] 李升波 徐晨翔 XIN Zhe;YU Zhou;GUO Qiangqiang;LIN Qingfeng;LI Shengbo;XU Chenxiang(College of Engineering,China Agriculture University,Beijing 100083,China;Department of Automotive Engineering,Tsinghua University,Beijing 100084,China;School of Transportation Science and Engineering,Beihang University,Beijing 100191,China)

机构地区:[1]中国农业大学工学院,北京100083 [2]清华大学汽车工程系,北京100084 [3]北京航空航天大学交通科学与工程学院,北京100191

出  处:《清华大学学报(自然科学版)》2018年第7期684-692,共9页Journal of Tsinghua University(Science and Technology)

基  金:国家自然科学基金面上项目(51575293);国家自然科学基金优秀青年科学基金项目(51622504);“十三五”国家重点研发计划(2016YFB0100906);国家国际科技合作专项资助(2016YFE0102200)

摘  要:针对网联汽车在多交叉口工况的通行过程,提出了一种多信号灯配时已知条件下的节油驾驶求解方法,并建立了相应的驾驶策略。将两信号灯下的节油策略辨识问题构建为约束型最优控制问题,该问题以发动机油耗为性能指标,以车辆纵向动力学模型为状态方程,并考虑了车辆性能约束、环境约束等。为求解该问题,提出了以动态规划为核心的反向递推计算方法,发现了车辆加速-匀速-减速的3段式节油行驶模式。以此为基础,将车辆在多信号灯下的节油驾驶策略辨识问题转化为有向图的最短路径求解问题,并采用Floyd-Warshall最短路径算法进行求解,得到了各交叉口道路限速相同及不同工况下的车辆节油驾驶策略。This paper describes a fuel-saving driving strategy for multiple intersections with known signal times.The fuel-saving strategy with two signals is constructed as a constrained optimal control problem with the vehicle longitudinal dynamics model as the state equations and with the vehicle physical performance and environmental conditions as constraints. A reverse recursive calculational method based on dynamic programming is used to solve the problem with an accelerate-cruise-decelerate fuel-saving driving strategy.The fuel-saving modes for two intersections are then extended to multiple intersections as a shortest path problem solved by the Floyd-Warshall algorithm.A fuel-saving driving strategy is then developed for multiple intersections with the same or different speed limits.

关 键 词:汽车燃料经济性 网联汽车 节油驾驶 交叉口 

分 类 号:U461.8[机械工程—车辆工程]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象