A Forward-Looking Stochastic Fleet Assessment Model for Analyzing the Impact of Uncertainties on Light-Duty Vehicles Fuel Use and Emissions

Paper #:
  • 2012-01-0647

  • 2012-04-16
  • 10.4271/2012-01-0647
Bastani, P., Heywood, J., and Hope, C., "A Forward-Looking Stochastic Fleet Assessment Model for Analyzing the Impact of Uncertainties on Light-Duty Vehicles Fuel Use and Emissions," SAE Int. J. Engines 5(2):452-468, 2012, https://doi.org/10.4271/2012-01-0647.
Transport policy research seeks to predict and substantially reduce the future transport-related greenhouse gas emissions and fuel consumption to prevent negative climate change impacts and protect the environment. However, making such predictions is made difficult due to the uncertainties associated with the anticipated developments of the technology and fuel situation in road transportation, which determine the total fuel use and emissions of the future light-duty vehicle fleet. These include uncertainties in the performance of future vehicles, fuels' emissions, availability of alternative fuels, demand, as well as market deployment of new technologies and fuels. This paper develops a methodology that quantifies the impact of uncertainty on the U.S. transport-related fuel use and emissions by introducing a stochastic technology and fleet assessment model that takes detailed technological and demand inputs. This model stochastically calculates the probability density functions for fuel use and emissions over time by propagating and calculating the effect of input uncertainties throughout fleet calculations. The fleet turn over is tracked based on the calendar year, vehicle model year, the market penetration rate of advanced technologies and fuels, and the scrappage rate of vehicles on the road. Full life-cycle emissions of fuels are projected and tracked in this model. Three carefully chosen illustrative examples are assessed using the developed methodology in this paper. The results show the probability distribution of the total light-duty vehicle fleet fuel use and emissions out to year 2050, including the mean, mode, standard deviation, spread, and confidence interval of these outputs in the near to long term. The major contributors to the fleet fuel use and emissions are also identified and ranked. These include vehicle scrappage rate, new vehicle sales, emphasis on reducing fuel consumption, and fuel consumption of naturally aspirated spark ignition vehicles. The major contributing variables and uncertainties to fuel use and emissions change over the time period 2020 to 2050. The findings in this paper indicate that uncertainties in the future fleet fuel use and emissions are significant and need to be taken into consideration when choosing amongst alternative fuel and emissions reduction pathways, in the light of their possible consequences.
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