PHEV Energy Use Estimation: Validating the Gamma Distribution for Representing the Random Daily Driving Distance

Journal Article · Sun Jan 01 04:00:00 EST 2012 · Transportation Research Record

DOI:https://doi.org/10.3141/2287-05· OSTI ID:1056911

Lin, Zhenhong ^[1]; Dong, Jing ^[1]; Liu, Changzheng ^[1]; Greene, David L ^[1]

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1. ORNL

The petroleum and electricity consumptions of plug-in hybrid electric vehicles (PHEVs) are sensitive to the variation of daily vehicle miles traveled (DVMT). Some studies assume DVMT to follow a Gamma distribution, but such a Gamma assumption is yet to be validated. This study finds the Gamma assumption valid in the context of PHEV energy analysis, based on continuous GPS travel data of 382 vehicles, each tracked for at least 183 days. The validity conclusion is based on the found small prediction errors, resulting from the Gamma assumption, in PHEV petroleum use, electricity use, and energy cost. The finding that the Gamma distribution is valid and reliable is important. It paves the way for the Gamma distribution to be assumed for analyzing energy uses of PHEVs in the real world. The Gamma distribution can be easily specified with very few pieces of driver information and is relatively easy for mathematical manipulation. Given the validation in this study, the Gamma distribution can now be used with better confidence in a variety of applications, such as improving vehicle consumer choice models, quantifying range anxiety for battery electric vehicles, investigating roles of charging infrastructure, and constructing online calculators that provide personal estimates of PHEV energy use.

• Research Organization: Oak Ridge National Laboratory (ORNL); National Transportation Research Center
• Sponsoring Organization: EE USDOE - Office of Energy Efficiency and Renewable Energy (EE)
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 1056911
• Journal Information: Transportation Research Record, Journal Name: Transportation Research Record Journal Issue: 2287 Vol. 2287; ISSN 0361-1981
• Country of Publication: United States
• Language: English

Related Subjects

energy use
plug-in hybrid electric vehicle
travel data
travel pattern