计算机科学
排队
布线(电子设计自动化)
集合(抽象数据类型)
排队论
最短路径问题
电动汽车
充电站
运筹学
数学优化
实时计算
计算机网络
工程类
数学
图形
理论计算机科学
功率(物理)
物理
量子力学
程序设计语言
作者
Sven Schoenberg,Falko Dressler
出处
期刊:IEEE transactions on intelligent vehicles
[Institute of Electrical and Electronics Engineers]
日期:2023-01-01
卷期号:8 (1): 95-107
被引量:15
标识
DOI:10.1109/tiv.2022.3140894
摘要
Electric vehicles are becoming more popular all over the world. With increasing battery capacities and a growing fast-charging infrastructure, they are becoming suitable for long-distance travel. However, queues at charging stations could lead to long waiting times, making efficient route planning even more important. In general, optimal multi-objective route planning is extremely computationally expensive. We propose an adaptive charging and routing strategy, which considers driving, waiting, and charging time. For this, we developed a multi-criterion shortest-path search algorithm using contraction hierarchies. To further reduce the computational effort, we precompute shortest-path trees between the known locations of the charging stations. We propose a central charging station database (CSDB) that helps estimating waiting times at charging stations ahead of time. This enables our adaptive charging and routing strategy to reduce these waiting times. In an extensive set of simulation experiments, we demonstrate the advantages of our concept, which reduces average waiting times at charging stations by up to $97 \,\%$ . Even if only a subset of the cars uses the CSDB approach, we can substantially reduce waiting times and thereby the total travel time of electric vehicles.
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