An Investigation on Vehicle Fuel Consumption Optimization Strategy Based on Scenario Information

X. Li, Mingxin Kang
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Abstract

The rapid development of vehicle-to-everything (V2X) and intelligent control technologies brings new opportunities and challenges to the traditional automotive control architecture. More driving information about traffic scenarios and ambient events such as the road slope, the traffic light timing is possible to be obtained via V2X system. And then, those traffic information will be extracted by individual vehicle’s controller and be further utilized to design the optimal control strategy. Fuel economy performance and time losses for waiting for the traffic red light are the two main concerns by most drivers. In order to obtain a satisfactory fuel economy performance and lower traveling time loss, this paper investigates an eco-driving problem for road vehicles when assuming the information of the traffic light ahead is prior known. The optimization problem by balancing the fuel consumption and time loss is designed and meanwhile the time phase of the traffic light is also considered. The optimization problem is firstly solved with the dynamic programming (DP) algorithm. Preliminary simulations have been implemented and the simulation results demonstrate the potential ability in improvement of the fuel economy performance. Moreover, an equivalent problem is formulated under the switching control system framework, to guarantee the hard constraint of the red light. The equivalent problem provides an interesting topic for the open discussion.
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基于场景信息的汽车油耗优化策略研究
车联网(V2X)和智能控制技术的快速发展给传统的汽车控制体系结构带来了新的机遇和挑战。通过V2X系统可以获得更多关于交通场景和环境事件的驾驶信息,如道路坡度,红绿灯定时。然后,这些交通信息将被单独的车辆控制器提取,并进一步用于设计最优控制策略。燃油经济性和等待交通红灯的时间损失是大多数司机关心的两个主要问题。为了获得满意的燃油经济性和较低的行驶时间损失,本文研究了假设前方交通灯信息事先已知的道路车辆的生态驾驶问题。设计了平衡油耗和时间损失的优化问题,同时考虑了交通灯的时间相位。首先用动态规划(DP)算法求解优化问题。进行了初步的仿真,仿真结果表明了该方法在提高燃油经济性方面的潜在能力。并在切换控制系统框架下建立了等效问题,保证了红灯的硬约束。等效问题为公开讨论提供了一个有趣的话题。
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