Heavy-duty diesel trucks are critical to goods movement in the United States and their demand is expected to increase significantly in the near future. Although diesel engines are more fuel efficient than their gasoline counterpart, their abundant use in the freight transportation sector makes them a significant source of carbon dioxide (CO2), the most significant anthropogenic greenhouse gas (GHG). With the increasing concern over limiting GHG emissions, much attention has been put on heavy duty trucks and improving their fuel economy as well as reducing their CO2 emissions. Most ofthe focus to date has been placed on specific vehicle technology and alternative fuels. However, another key area that is often overlooked is operational variability associated with heavy duty truck use and how vehicle operation can be modified to reduce CO2. This paper examines some of these truck operational variables including vehicle speed, road grade, vehicle weight, and roadway facility type. To examine these variables, we have collected a large amount of on-road heavy-duty truck data using a state-of-the-art mobile emission laboratory. This lab collects real-world fuel economy and emissions data for a variety of driving conditions. In addition, a state-of-the-art modal emission model for heavy duty diesel trucks is utilized in the analysis.
Abstract