Development of a new tank-to-wheels methodology for energy use and green house gas emissions analysis based on vehicle fleet modeling

Abstract

Background, aim and scope

Tank-to-Wheels (TtW) makes the largest contribution to the total Well-to-Wheels (WtW) energy consumption and greenhouse gas (GHG) emissions from fossil-derived transportation fuels. The most commonly adopted TtW methodologies to obtain vehicle energy consumption, energy efficiency, and GHG emissions used to date all have significant limitations. A new TtW methodology, which combines micro-scale virtual vehicle simulation with macro-scale fleet modeling, is proposed in this paper. The models capabilities are demonstrated using a case study based on data from the passenger car sector in Great Britain.

Methods

A simplified internal combustion engine model was developed in-house to simulate engine behaviors across a wide range of engine capacities and technologies. Vehicle simulation was then carried out using the efficiency map output by the simplified engine model for any given gasoline or diesel engine; the simulation was validated for 37 vehicles available on the UK market in terms of their vehicle-certification fuel consumption, with a discrepancy generally within 3%. Real-world fleet and driving data from the Great Britain’s car fleet was extracted from the Transport Statistics Great Britain (TSGB) database between 2001 and 2007TSGB 2001–2007. A virtual fleet was constructed with the validated virtual vehicles to represent the real-world passenger car fleet in terms of its composition and operating characteristics. This fleet model was shown to match the real-world fleet-averaged fuel consumption within 3% for the gasoline fleet and within 6% for the diesel fleet. Finally, several scenarios were analyzed using the validated fleet model, covering a projection for 2008, driving pattern, lubrication, and fuel. The vehicle-to-vehicle variation was found to be significant in some scenarios, indicating that a fleet-based methodology would be more rigorous and flexible.

Discussion

Energy consumption and CO₂ emission figures from previous, well-recognized Europe-oriented studies (e.g., the 2008 JRC/EUCAR/CONCAWE study) were significantly lower than the TSGB real-world results based on the new TtW methodology. It is apparent that using a single vehicle to represent the whole fleet could be misleading; in particular, the relative energy efficiency and CO₂ emission of diesel over gasoline cars might follow a different trend with time for the real-world fleet from that shown in previous studies.

Conclusions

Future WtW studies can benefit from the modeling toolset and methodology reported herein in a number of ways:

• TtW analysis can be carried out

• thoroughly—on a fleet basis

• independently—involving less proprietary information

• impartially—not concentrating on a specific vehicle model

• and flexibly—allowing detailed analysis of physics, chemistry, and vehicle component performance.

• When comparing different WtW energy pathways, e.g., gasoline vs. diesel passenger cars or natural gas vs. bio-diesel fuelled busses, the absolute aggregate fleet impact can be investigated—conclusions based on a single vehicle may overlook vehicle-to-vehicle variations and potentially mislead policy making.

• Using the virtual fleet database as a platform, a large number of scenarios can be analyzed and detailed impact of fuels properties, vehicle technologies and driving patterns on WtW results investigated. The models will evolve in time together with the researchers’ knowledge base and data base.

Recommendations and perspectives

The virtual engine/vehicle/fleet model developed in this work can readily be expanded and upgraded in the future, in terms of model details, coverage, and data quality. The methodology itself is generically applicable to any defined fleet (passenger cars, commercial vehicles, etc.) with any operating characteristics at any given timeframe from any geographic region. Various subjects and their implications for fleet energy consumption and GHG emissions could be studied including, but not restricted to, the following:

• Fuels—injector/valve cleanliness, anti-knock properties, dieselization, bio-components, gaseous fuels etc.

• Engine/vehicle technology—friction and weight reduction, advanced combustion, hybridization etc.

• Driving pattern—vehicle loading, gear-shifting schedule, tire maintenance, cold start, etc.