论文标题
长途生态驾驶：重型卡车操作模式控制与集成的路坡预览
Long hauling eco-driving: heavy-duty trucks operational modes control with integrated road slope preview
论文作者
论文摘要
在本文中，基于有限数量的带有相应齿轮换档的驾驶模式的重型卡车（HDT）的完整生态驾驶策略，以应对不同的路线事件和路线坡度数据。对于燃料消耗和行程持续时间，该问题被称为最佳控制问题，并使用Pontryagin最低原理（PMP）算法解决了路径搜索问题，因此可以实时在线进行计算。开发的生态驾驶援助系统（EDAS）为驾驶员提供了速度轮廓和一系列驾驶模式（和齿轮）建议，而无需积极控制HDT（循环中的人），并且实际上允许驾驶员的上下文反馈成型。仿真结果表明，开发的方法能够根据已知的道路事件和坡度信息为完整路线提供速度曲线，同时满足所有卡车操作约束。
In this paper, a complete eco-driving strategy for heavy-duty trucks (HDT) based on a finite number of driving modes with corresponding gear shifting is developed to cope with different route events and with road slope data. The problem is formulated as an optimal control problem with respect to fuel consumption and trip duration, and solved using a Pontryagin minimum principle (PMP) algorithm for a path search problem, such that computations can be carried out online, in real-time. The developed eco-driving assistance system (EDAS) provides a velocity profile and a sequence of driving modes (and gears) recommendation to the driver, without actively controlling the HDT (human in the loop) and, in practice, allows contextual feedback incorporation from the driver for safety. Simulation results show that the developed methodology is able to provide a velocity profile for a complete route based on known road events and slope information while satisfying all truck operational constraints.
