卡车最佳减速和换档生态驾驶PMP算法的设计和评估
Design and assessment of an eco--driving PMP algorithm for optimal deceleration and gear shifting in trucks
摘要：
本文设计了一种基于有限驾驶模式切换的卡车最优减速和换挡的生态驾驶庞特里亚金最大值原理（PMP）算法。PMP算法在IPG TruckMaker交通模拟器中作为生态驾驶辅助系统（EDAS）实施和评估。开发的EDAS策略通过优化的速度曲线降低了燃油消耗，并且在实践中，允许驾驶员为安全提供上下文反馈。此外，对驾驶模式的优化在计算上是廉价的，允许该方法被在线实时地使用。仿真结果表明，显着的燃料节省可以实现成比例的速度事件的数量和当前速度和最终期望的速度之间的差异，为每个事件。
英文摘要：
In this paper, an eco--driving Pontryagin maximum principle (PMP) algorithm is designed for optimal deceleration and gear shifting in trucks based on switching among a finite set of driving modes. The PMP algorithm is implemented and assessed in the IPG TruckMaker traffic simulator as an eco--driving assistance system (EDAS). The developed EDAS strategy reduces fuel consumption with an optimized velocity profile and, in practice, allows contextual feedback incorporation from the driver for safety. Furthermore, the optimization over driving modes is computationally inexpensive, allowing the methodology to be used online, in real--time. Simulation results show that significant fuel savings can be achieved proportional to the number of velocity events and the difference between current velocity and final desired velocity for each event.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
