Quantifying a cellular automata simulation of electric vehicles
Quantifying a cellular automata simulation of electric vehicles
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DOI：
10.1016/j.physa.2014.08.007
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发表时间：
2014-12
影响因子：
3.3
通讯作者：
G. Hill;M. Bell;P. Blythe
中科院分区：
文献类型：
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作者：
G. Hill;M. Bell;P. Blythe
在这项工作中，Nagel–Schreckenberg (NS) 元胞自动机用于模拟基本的循环道路网络。 SwitchEV 是一项现实世界的电动汽车试验，收集了两年多的详细电动汽车数据，其结果用于量化 NS 自动机的结果，展示了与实验结果中观察到的类似的功耗行为。特别是，电动汽车的效率随着车辆密度的增加而降低，部分原因是电动汽车在低速时效率降低，但也由于速度变化所固有的能量消耗。进一步的工作展示了引入空间限制速度限制的结果。一般来说，可以看出，空间瞬态事件引起的拥堵会通过道路网络传播回来，并改变模拟车辆在速度限制之前和之后的能量和效率曲线。限速上游的车辆显示出能源使用量减少和效率提高，而下游车辆在加速远离限速时显示出能源使用量最初大幅增加。
Within this work the Nagel–Schreckenberg (NS) cellular automata is used to simulate a basic cyclic road network. Results from SwitchEV, a real world Electric Vehicle trial which has collected more than two years of detailed electric vehicle data, are used to quantify the results of the NS automata, demonstrating similar power consumption behavior to that observed in the experimental results. In particular the efficiency of the electric vehicles reduces as the vehicle density increases, due in part to the reduced efficiency of EVs at low speeds, but also due to the energy consumption inherent in changing speeds. Further work shows the results from introducing spatially restricted speed restriction. In general it can be seen that induced congestion from spatially transient events propagates back through the road network and alters the energy and efficiency profile of the simulated vehicles, both before and after the speed restriction. Vehicles upstream from the restriction show a reduced energy usage and an increased efficiency, and vehicles downstream show an initial large increase in energy usage as they accelerate away from the speed restriction.