We present a parametric analysis of factors that can influence advanced fuel and technology deployments in U.S. Class 7-8 trucks through 2050. The analysis focuses on the competition between traditional diesel trucks, natural gas vehicles (NGVs), and ultra-efficient powertrains. Underlying the study is a vehicle choice and stock model of the U.S. heavy-duty vehicle market. The model is segmented by vehicle class, body type, powertrain, fleet size, and operational type. We find that conventional diesel trucks will dominate the market through 2050, but NGVs could have significant market penetration depending on key technological and economic uncertainties. Compressed natural gas trucks conducting urban trips in fleets that can support private infrastructure are economically viable now and will continue to gain market share. Ultra-efficient diesel trucks, exemplified by the U.S. Department of Energy's SuperTruck program, are the preferred alternative in the long haul segment, but could compete with liquefied natural gas (LNG) trucks if the fuel price differential between LNG and diesel increases. However, the greatest impact in reducing petroleum consumption and pollutant emissions is had by investing in efficiency technologies that benefit all powertrains, especially the conventional diesels that comprise the majority of the stock, instead of incentivizing specific alternatives.
This report describes work performed for an Early Career Research and Development project. This project developed a heavy-duty vehicle (HDV) sector model to assess the factors influencing alternative fuel and efficiency technology adoption. This model builds on a Sandia light duty vehicle sector model and provides a platform for assessing potential impacts of technological advancements developed at the Combustion Research Facility. Alternative fuel and technology adoption modeling is typically developed around a small set of scenarios. This HDV sector model segments the HDV sector and parameterizes input values, such as fuel prices, efficiencies, and vehicle costs. This parameterization enables sensitivity and trade space analyses to identify the inputs that are most associated with outputs of interest, such as diesel consumption and greenhouse gas emissions. Thus this analysis tool enables identification of the most significant HDV sector drivers that can be used to support energy security and climate change goals.
In the coming decades, vehicle and fuel options and their supporting infrastructure must undergo significant transformations to achieve aggressive national targets for reducing petroleum consumption and lowering greenhouse gas (GHG) emissions. Vehicle electrification, advanced biofuels, natural gas, and hydrogen fuel cells are among the promising technology options that are being explored as future alternatives. A number of recent U.S. studies have examined how a mix of technology and policy options can contribute to the aggressive goals of 50- 80% reduction in petroleum consumption and 80% reduction in GHG emissions by 2050. These include reports issued by the National Petroleum Council, National Academies, and U.S. Department of Energy. While these studies all generally point to the need for a portfolio of technologies for the transportation sector, they do not draw the same set of conclusions for the portfolio mix. Moreover, they were commissioned for a variety of reasons, applied different modelling and analytical approaches in their assessments, and used a variety of assumptions in reaching their findings and recommendations. Using four recent major U. S. scenario analyses, this paper will illustrate several factors that can influence the interpretation of their results. Consideration of the underlying technology and policy assumptions, analytical approaches, and presentation of results can enable a more robust comparison across projections for the vehicle and fuel mix.