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A trajectory-based energy consumption estimation method considering battery degradation for an urban electric vehicle network

机译:一种基于轨迹的能耗估算方法

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As a cost-effective and environmental-friendly transport means, electric vehicle (EV) has received widespread attention in the recent decade. The increasing market share and wider adoption of EV in transportation systems also bring about the energy use issues. In this paper, we propose a method to estimate network-wide EV energy consumption by taking into account battery degradation. We first derive unit energy consumption functions with respect to the battery degradation rate by quadratic regression method using EV operational data in the US. We then put forward an easy-to-implement and tangible method to estimate EV network energy consumption based on EV trajectories and the derived unit energy consumption function. In detail, EVs' battery degradation rates are assumed to follow a given and known probability distribution and daily travel mileage of each EV is derived from EV trajectories. Based on these, we can get the expected total energy consumption in the network. We also propose a prorated assignment approach to determine the expected energy consumed by EVs through each EV charging point based on the estimated temporal-spatial charging demand distribution from EVs' trajectories. A case study in Singapore is demonstrated in the end and the importance of incorporating battery degradation is highlighted. The results reveal that overlooking battery degradation would lead to more than 10% of estimation error in energy consumption estimation.
机译:电动汽车(EV)作为一种经济高效且环保的运输工具,在最近十年中受到了广泛关注。不断增长的市场份额和电动汽车在交通系统中的广泛采用也带来了能源使用问题。在本文中,我们提出了一种通过考虑电池退化来估算网络范围内EV能耗的方法。我们首先使用美国的EV运营数据,通过二次回归方法得出与电池退化率有关的单位能耗函数。然后,我们提出了一种易于实现的有形方法,可以根据电动汽车的轨迹和推导的单位能耗函数估算电动汽车的网络能耗。详细地,假设电动汽车的电池退化率遵循给定和已知的概率分布,并且每个电动汽车的每日行驶里程是从电动汽车的轨迹得出的。基于这些,我们可以获得网络中预期的总能耗。我们还提出了一种按比例分配的方法,以根据从电动汽车的轨迹估计的时空充电需求分布,确定电动汽车通过每个电动汽车充电点所消耗的预期能量。最后在新加坡进行了案例研究,并强调了整合电池退化的重要性。结果表明,忽略电池退化会导致能耗估算中超过10%的估算误差。

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