Electric vehicle cost, emissions, and water footprint in the United States: Development of a regional optimization model

Electric vehicle cost, emissions, and water footprint in the United States: Development of a regional optimization model
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DOI:
10.1016/j.energy.2015.05.152
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发表时间:
2015-09
期刊:
影响因子:
9
通讯作者:
M. Noori;Stephanie Gardner;O. Tatari
M. Noori;Stephanie Gardner;O. Tatari
中科院分区:
工程技术1区
文献类型:
--
作者:
M. Noori;Stephanie Gardner;O. Tatari

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电动汽车的生命周期成本和环境影响非常不确定,但对于制定政策决策至关重要。这项研究提出了一个新的模型,称为电动汽车区域优化器,以模拟这种不确定性,并预测2030年美国不同地区的动力传动系统的最佳组合。首先,考虑到其固有的不确定性,内燃机汽车,汽油混合动力汽车,和三种不同的电动汽车类型(汽油插电式混合动力汽车,汽油增程式电动汽车,全电动汽车)的生命周期成本和生命周期环境排放进行了评估。然后,环境破坏成本和水足迹的研究动力传动系统进行了估计。此外,使用探索性建模和分析方法,在生命周期成本,环境损害成本和水足迹的研究车辆类型的不确定性建模为不同的美国电网区域。最后,将优化模型与探索性建模和分析相结合,以找到2030年美国每个地区不同车型的理想组合。这项研究的结果将有助于政策制定者和交通规划者为电动汽车的涌入做好准备。
The life cycle cost and environmental impacts of electric vehicles are very uncertain, but extremely important for making policy decisions. This study presents a new model, called the Electric Vehicles Regional Optimizer, to model this uncertainty and predict the optimal combination of drivetrains in different U.S. regions for the year 2030. First, the life cycle cost and life cycle environmental emissions of internal combustion engine vehicles, gasoline hybrid electric vehicles, and three different Electric Vehicle types (gasoline plug-in hybrid electric vehicles, gasoline extended range electric vehicle, and all-electric vehicle) are evaluated considering their inherent uncertainties. Then, the environmental damage costs and the water footprint of the studied drivetrains are estimated. Additionally, using an Exploratory Modeling and Analysis method, the uncertainties in the life cycle cost, environmental damage cost, and water footprint of studied vehicle types are modeled for different U.S. electricity grid regions. Finally, an optimization model is coupled with Exploratory Modeling and Analysis to find the ideal combination of different vehicle types in each U.S. region for the year 2030. The findings of this research will help policy makers and transportation planners to prepare our nation's transportation system for the influx of electric vehicles.