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On Scalability of Electric Car Sharing in Smart Cities

机译:智慧城市中电动汽车共享的可扩展性

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In this paper we analyze which are the design options that would impact a free floating electric car sharing system performance and costs, studying how the system would scale with an increase in the intensity of the demand. We consider the case study of the city of Turin, for which we leverage hundred of thousands of actual rentals from a (combustion-based) car sharing system to derive an accurate demand model. Armed with this, we consider the transition to electric cars and the need to deploy a charging station infrastructure.Using a realistic simulator, we present the impact of system design options, like the number of charging poles, their allotment, and the number of cars. We first consider performance indicators, like fraction of satisfied demand and working hours system has to spend to bring to charge vehicles. Then we map these figures into revenues and costs, projecting economical indicators. At last, we investigate the scalability of the whole system, i.e., how performance and costs scale when the demand increases. Our results show that concentrating the charging stations in key places is instrumental to optimize car distribution in the city to better intercept the demand. Considering system scalability, the charging infrastructure must intuitively grow proportionally with the mobility demand. Interestingly instead, the fleet size can grow much slower, showing some nice economy of scale gains.
机译:在本文中,我们分析了哪些设计选项会影响自由浮动电动汽车共享系统的性能和成本,并研究该系统如何随着需求强度的增加而扩展。我们考虑都灵市的案例研究,为此我们利用(基于燃烧的)汽车共享系统的数十万笔实际租金来推导准确的需求模型。为此,我们考虑了向电动汽车的过渡以及部署充电站基础设施的需求。使用逼真的模拟器,我们介绍了系统设计选项的影响,例如充电极的数量,其分配和汽车数量。 。我们首先考虑性能指标,例如满足需求的比例和工作时间系统必须花费才能为车辆充电。然后,我们将这些数字映射为收入和成本,并预测经济指标。最后,我们研究了整个系统的可扩展性,即,当需求增加时性能和成本如何扩展。我们的结果表明,将充电站集中在关键位置有助于优化城市中的汽车分配,从而更好地满足需求。考虑到系统的可伸缩性,充电基础设施必须直观地与移动性需求成正比地增长。相反,有趣的是,机队的规模增长得慢得多,显示出规模经济增长的良好效果。

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