论文标题
运输网络中插电式混合动力汽车的生态路线和电力训练控制
Combined Eco-Routing and Power-Train Control of Plug-In Hybrid Electric Vehicles in Transportation Networks
论文作者
论文摘要
我们研究了插电式混合动力汽车（PHEV）的生态路由问题，以最大程度地降低整体能源消耗成本。我们提出了一种算法，该算法可以同时计算PHEV的能量最佳路线（Eco-Route），并在此路线上计算出最佳的功率训练策略。为了显示我们方法在实践中的有效性，我们使用此处地图API根据波士顿市的流量数据应用了我们的算法，并具有超过110,000个链接。此外，我们使用从交通模拟器（SUMO）收集的速度轮廓作为高保真能源模型的输入来验证生态路由算法的性能，以计算能耗成本。我们的结果显示，对于算法，PHEV的PHEV节省大量节省（约12％）。
We study the problem of eco-routing for Plug-In Hybrid Electric Vehicles (PHEVs) to minimize the overall energy consumption cost. We propose an algorithm which can simultaneously calculate an energy-optimal route (eco-route) for a PHEV and an optimal power-train control strategy over this route. In order to show the effectiveness of our method in practice, we use a HERE Maps API to apply our algorithms based on traffic data in the city of Boston with more than 110,000 links. Moreover, we validate the performance of our eco-routing algorithm using speed profiles collected from a traffic simulator (SUMO) as input to a high-fidelity energy model to calculate energy consumption costs. Our results show significant energy savings (around 12%) for PHEVs with a near real-time execution time for the algorithm.
