Modeling the effects of congestion on fuel economy for advanced power train vehicles

Abstract

Fuel-speed curves (FSC) are used to account for the aggregate effects of congestion on fuel consumption in transportation scenario analysis. This paper presents plausible FSC for conventional internal combustion engine (ICE) vehicles and for advanced vehicles such as hybrid electric vehicles, fully electric vehicles (EVs), and fuel cell vehicles (FCVs) using a fuel consumption model with transient driving schedules and a set of 145 hypothetical vehicles. The FSC shapes show that advanced power train vehicles are expected to maintain fuel economy (FE) in congestion better than ICE vehicles, and FE can even improve for EV and FCV in freeway congestion. In order to implement these FSC for long-range scenario modeling, a bounded approach is presented which uses a single congestion sensitivity parameter. The results in this paper will assist analysis of the roles that vehicle technology and congestion mitigation can play in reducing fuel consumption and greenhouse gas emissions from motor vehicles. IntroductionTraffic congestion is ubiquitous and increasing in urban areas, leading to longer travel times, lower average speeds, and increased vehicle speed variability. These outcomes influence vehicle engine operating loads and operating duration, which in turn have an impact on fuel efficiency. At the same time, the passenger vehicle fleet continues to evolve with advanced power train types such as hybrid electric vehicles (HEVs), fuel cell vehicles (FCVs), and fully electric vehicles (EVs). This paper addresses how these advanced vehicle technologies will respond to congestion, in terms of fuel efficiency.Motor vehicle fuel efficiency can be expressed as fuel economy (FE) -in travel distance per unit volume of fuel -in the USA as miles per gallon (mpg). Fuel-speed curves (FSC) generalize the relationship between FE and congestion as the average FE at a given average travel speed, including typical acceleration and deceleration activity (usually for specific vehicle and roadway types). The average speed variable in FSC is a proxy for congestion level, indicative of both average speed and speed variability for archetypal conditions. Thus, FSC can serve to estimate the effects of congestion on aggregate fuel consumption in macroscopic traffic and transportation models.Existing research on FSC for conventional internal combustion engine (ICE) vehicles indicates that increasing levels of congestion -with lower average speeds -lead to

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