Estimating region-specific fuel economy in the United States from real-world driving cycles. (September 2020)

• Record Type: Journal Article
• Authors: Borlaug, Brennan; Holden, Jacob; Wood, Eric; Lee, Byungho; Fink, Justin; Agnew, Scott; Lustbader, Jason
• Is Part Of: Transportation research. Volume 86(2020)
• Publication Date: 2020-09
• Subjects: Driving cycle -- Driving patterns -- Driving conditions -- Fuel consumption -- Fuel economy -- Simulation; Transportation -- Research -- Periodicals; Transportation -- Environmental aspects -- Periodicals; 354.76
• DOI: 10.1016/j.trd.2020.102448
• Languages: English
• ISSNs: 1361-9209

Abstract

Highlights: Analyzed U.S. driving data from over 10, 000 vehicles and 1 million miles travelled. Presents six driving cycles, representative of real-world U.S. driving segments. Observed key differences between six cycles and pre-existing legislative cycles. Developed method for estimating region-specific fuel consumption rates. Regional fuel consumption rates vary over 11% due to driving pattern differences. Abstract: This paper describes a method for estimating region-specific real-world light-duty vehicle fuel economy in the United States that is unique in both the size and representativeness of real-world driving that was considered, and for its ability to model regional variations in driving patterns. Over one million miles of national driving data were used to select real-world cycles representative of observed trip categories. The six cycles were compared to U.S. legislative cycles, revealing some key differences. Finally, a set of cycle weighting factors for 533 separate U.S. regions was derived from annual traffic statistics. Applying this method, it was found that regional fuel economy varies due to differences in driving patterns alone and that rural driving patterns lead to improved fuel economy (for conventional vehicles). The driving cycles and regional weighting factors described here are useful for testing and simulation studies, specifically those sensitive to regional variations in driving patterns.