Modeling the Effects of Congestion on Fuel

35 This paper describes research undertaken to establish plausible fuel-speed curves (FSC) for 36 hypothetical advanced powertrain vehicles. These FSC are needed to account for the effects of 37 congestion in long-term transportation scenario analysis considering fuel consumption and 38 emissions. We use the PERE fuel consumption model with real-world driving schedules and a 39 range of vehicle characteristics to estimate fuel economy (FE) in varying traffic conditions for 40 light-duty internal combustion engine (ICE) vehicles, hybrid gas-electric vehicles (HEV), fully 41 electric vehicles (EV), and fuel cell vehicles (FCV). FSC are fit to model results for each of 145 42 hypothetical vehicles. Analysis of the FSC shows that advanced powertrain vehicles are expected 43 to perform proportionally better in congestion than ICE vehicles (when compared to their 44 performance in free-flow conditions). HEV are less sensitive to average speed than ICE vehicles, 45 and tend to maintain their free-flow FE down to 20 mph. FE increases for EV and FCV from 46 free-flow conditions down to about 20-30 mph. Beyond powertrain type differences, relative FE 47 in congestion is expected to improve for vehicles with less weight, smaller engines, higher 48 hybrid thresholds, and lower accessory loads (such as air conditioning usage). Relative FE in 49 congestion also improves for vehicle characteristics that disproportionately reduce efficiency at 50 higher speeds, such as higher aerodynamic drag and rolling resistance. In order to implement 51 these FSC for scenario analysis, we propose a bounded approach based on a qualitative 52 characterization of the future vehicle fleet. The results presented in this paper will assist analysis 53 of the roles that vehicle technology and congestion mitigation can play in reducing fuel 54 consumption and emissions from roadway travel. 55 56