重庆理工大学学报(自然科学) ›› 2023, Vol. 37 ›› Issue (1): 280-290.

• 数学·统计学 • 上一篇    下一篇

面向城市信号灯环境的多模混合动力汽车经济性驾驶研究

张葆青,陈 爽,辛越峰   

  1. 中国工程物理研究院流体物理研究所,四川 绵阳 62199
  • 出版日期:2023-02-16 发布日期:2023-02-16
  • 作者简介:张葆青,男,硕士,高级工程师,主要从事复杂机电系统设计研究,Email:707680795@qq.com;通讯作者 陈爽, 男,高级工程师,主要从事复杂机电系统设计研究,Email:1321174@qq.com。

Research on economical driving of multi-mode hybrid electric vehicles facing urban traffic lights

  • Online:2023-02-16 Published:2023-02-16

摘要: 以智能网联环境下的多模混合动力汽车作为研究对象,开展了面向城市道路信号 交叉口的经济性驾驶研究。首先,基于车联网信息获取信号灯相位与计时数据,根据信号灯位 置与道路限速等约束搭建多个信号交叉口路网模型,建立了面向控制的多模混合动力系统部件 模型与整车能耗模型;其次,基于庞特里亚金极小值原理解决单车经济性驾驶问题,针对红绿灯 路口进行场景分析,规划车辆在不停车通过条件下的有效速度范围,分析了连续信号交叉口的 经济性速度优化问题;最后,基于模型预测控制求解多模混合动力汽车的最优能量管理问题,同 时引入模式切换惩罚项以提高多模混合动力系统的运行平顺性。与全局最优的动态规划型能 量管理相比,新控制策略取得了 3.767L/100km的近优燃油经济性。

关键词: 交通信号灯, 经济性速度规划, 多模混合动力汽车, 模式切换, 能量管理

Abstract: This paper takes a multi-mode hybrid electric vehicle (HEV) in an intelligent connected environment as the research object and researches economic driving for urban road traffic intersections. Firstly, the phase and timing data of the signal lights are obtained based on the information from the Internet to Vehicles, and a road network model of multiple signal intersections is built according to the constraints such as the position of the signal lights and the speed limit. Meanwhile, a control-oriented multi-mode hybrid powertrain component model and an energy consumption model for assembled cars are established. Secondly, economical driving of a single vehicle is solved based on the Pontryagin minimum principle (PMP). The scenario analysis of the traffic light intersections is performed, the effective speed range of the vehicle without stopping is planned, and the economical speed optimization of continuous signal intersections is analyzed. Finally, the optimal energy management strategy (EMS) for the multi-mode hybrid electric vehicle is solved based on model predictive control (MPC), and the penalty term about mode switching is introduced to improve the smoothness of the multi-mode hybrid power system. Compared with the dynamic programming-based energy management which belongs to the global optimum, the proposed control strategy achieves a near-optimal fuel economy of 3.767 L/100 km.

中图分类号: 

  • U461.2