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原文传递 Tool to Predict Fleet-Wide Heavy-Duty Vehicle Fuel-Saving Benefits from Low Rolling Resistance Tires.

题名：	Tool to Predict Fleet-Wide Heavy-Duty Vehicle Fuel-Saving Benefits from Low Rolling Resistance Tires.
作者：	Gbologah, F. E.; Rodgers, M. O.; Li, H.
关键词：	Rolling resistance tires, Combustion, Vehicle payload, Aerodynamic drag, Road grade, Duration of acceleration
摘要：	The cost of fuel represents a major portion of the costs of operating on-road heavy-duty vehicles (HDV). According to the American Transportation Research Institute, fuel costs alone amounted to about 25 percent of truck operating costs in 2015. Within the U.S. on-road transportation sector HDVs consume a disproportionately high amount of the total refined petroleum-based fuel and carbon dioxide emissions from consumption of this fuel were estimated to be equivalent to over 400 million metric tons. HDVs also contributed a disproportionately high 2.5 million short tons of Oxides of Nitrogen (NOx) emissions, emitted as a by-product of fuel combustion in on-road vehicle engines. NOx is a precursor of ozone, which is an air pollutant harmful to humans, plants, and animals. Over the next couple of decades, the total energy demand from the HDV sector will likely increase due to forecasted growth in freight demand in many global markets, including the United States, and much of this energy will continue to be provided by fossil fuels. Therefore, carbon dioxide emissions from the HDV sector are also expected to increase in the absence of effective mitigating measures to reduce the sectors reliance on fossil fuels. Along with other fuel-saving technologies, the United States Environmental Protection Agency identified the use of Low Rolling Resistance (LRR) tires as an effective method of reducing fuel consumption. It is estimated that LRR tires can improve fuel economy in HDV by about 10 percent. However, adoption of LRR faces many barriers and the most fundamental of these barriers relate to potential performance uncertainties under real-world operating conditions. Previous published decision support tools developed to help fleet operators and other stakeholders estimate the fuel-savings from LRR tires have been found to have limited accuracy due to inherent transient speed profiles in real-world operating cycles. In this study, we develop a tool to predict the fleet-wide fuel-saving benefits from low rolling resistance tires. Unlike previous studies, the developed tool is applicable to both stabilized speed operations and transient speed operations. The tool is based on empirical models that estimate the fuel consumption contribution from tires as a function of vehicle payload, aerodynamic drag, road grade, duration of acceleration, duration of deceleration and, and road facility type (freeway, major arterial, and minor arterial/local road). We limited the scope of the developed tool to tractor-trailers in the U.S. heavy-duty vehicle market, because the United States has the second largest HDV market in the world and tractor-trailers account for the largest share of the market. The tool was developed with data generated by simulating real-world heavy-duty vehicle operating cycles with Autonomie庐, the state-of-the-art model for automotive control-system design, and simulating vehicle energy consumption and performance. Autonomie庐 is a preferred vehicle simulation tool of the United States Department of Energy. The primary purpose of the Tool to Predict Fleet-Wide Heavy-Duty Vehicle Fuel-Saving from Low Rolling Resistance Tires is to assist fleet operators, regulatory agencies, and policy analysts in assessing the fuel consumption savings from low rolling resistance tires. To facilitate ease-of-use by stakeholders, the statistical empirical models are embedded in a Microsoft Excel庐 spreadsheet. Fleet managers can customize the tool to their specific fleet and the tool is designed to inform fleet operators about the benefits and costs of making low rolling resistance tire investments. In addition to fuel consumption estimates, the spreadsheet tool further estimates related emission reductions. In the future, this tool can be extended to other vehicle segments. The spreadsheet algorithms can also be developed into a web-based computer program in the future to facilitate online use of the tool.
报告类型：	科技报告