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Projecting adoption of truck powertrain technologies and CO_2 emissions in line-haul networks

机译：在线网络中采用卡车动力总成技术和CO_2排放量

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摘要

In this paper we present a mixed-integer linear program to represent the decision-making process for heterogeneous fleets selecting vehicles and allocating them on freight delivery routes to minimize total cost of ownership. This formulation is implemented to project alternative powertrain technology adoption and utilization trends for a set of line-haul fleets operating on a regional network. Alternative powertrain technologies include compressed (CNG) and liquefied natural gas (LNG) engines, hybrid electric diesel, battery electric (BE), and hydrogen fuel cell (HFC). Future policies, economic factors, and availability of fueling and charging infrastructure are input assumptions to the proposed modeling framework. Powertrain technology adoption, vehicle utilization, and resulting CO2 emissions predictions for a hypothetical, representative regional highway network are illustrated. A design of experiments (DOE) is used to quantify sensitivity of adoption outcomes to variation in vehicle performance parameters, fuel costs, economic incentives, and fueling and charging infrastructure considerations. Three mixed-adoption scenarios, including BE, HFC, and CNG vehicle market penetration, are identified by the DOE study that demonstrate the potential to reduce cumulative CO2 emissions by more than 25% throughout the period of study.
机译：在本文中，我们介绍了一个混合整数的线性程序，代表了非均质舰队选择车辆的决策过程，并在货运路线上分配它们，以最大限度地减少所有权总成本。该制定实施为项目替代动力总成技术采用和利用趋势，为一套在区域网络上运行的线路舰队。替代动力总成技术包括压缩（CNG）和液化天然气（LNG）发动机，混合电动柴油，电池电（BE）和氢燃料电池（HFC）。未来的政策，经济因素和加油和充电基础设施的可用性是对所提出的建模框架的输入假设。说明了动力总成技术采用，车辆利用率，并产生了一个假设，代表区域公路网络的二氧化碳排放预测。实验（DOE）的设计用于量化采用结果的敏感性，以对车辆性能参数，燃料成本，经济激励和加油和收费基础设施考虑的变化。通过DOE研究确定了三种混合采用情景，包括，HFC和CNG车辆市场渗透，证明在整个研究期间减少累积二氧化碳排放量超过25％的潜力。

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