Shortest feasible paths with charging stops for battery electric vehicles

M. Baum, Julian Dibbelt, Andreas Gemsa, D. Wagner, T. Zündorf
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引用次数: 62

Abstract

We study the problem of minimizing overall trip time for battery electric vehicles (EVs) in road networks. As battery capacity is limited, stops at charging stations may be inevitable. Careful route planning is crucial, since charging stations are scarce and recharging is time-consuming. We extend the Constrained Shortest Path (CSP) problem for EVs with realistic models of charging stops, including varying charging power and battery swapping stations. While the resulting problem is NP-hard, we propose a combination of algorithmic techniques to achieve good performance in practice. Extensive experimental evaluation shows that our approach (CHArge) enables computation of optimal solutions on realistic inputs, even of continental scale. Finally, we investigate heuristic variants of CHArge that derive high-quality routes in well below a second on sensible instances.
纯电动汽车带充电站的最短可行路径
研究了纯电动汽车在道路网络中的总行程时间最小化问题。由于电池容量有限,在充电站停车可能是不可避免的。仔细的路线规划是至关重要的,因为充电站很少,充电很耗时。我们将约束最短路径(CSP)问题扩展到具有实际充电停止模型的电动汽车,包括不同的充电功率和电池交换站。虽然由此产生的问题是np困难的,但我们提出了一种算法技术的组合,以在实践中获得良好的性能。广泛的实验评估表明,我们的方法(CHArge)能够在实际输入上计算最佳解决方案,甚至是大陆规模。最后,我们研究了CHArge的启发式变体,这些变体在一秒钟内推导出高质量的路由。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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