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This study explored the well-to-wheel greenhouse gas (GHG) emissions and total ownership costs for heavy-duty trucks (HDTs) with alternative drivetrains. The study compared 14 drivetrains for HDTs varying by fuel type, combustion technology, drivetrain topology, and electricity supply infrastructure. The authors employed GPS activity data for around 1,600 container tractor-trailer trucks operating mainly in British Columbia, Canada, to extract six distinct driving cycles grouped by average speed, elevation, distance, and location. A Monte Carlo simulation was conducted for a main freight long-haul route to determine the range of GHG emissions and total ownership costs for each drivetrain considering a range of uncertainties in several critical model parameters. Averaging the GHG emissions over all cycles for each drivetrain, the lowest GHG emissions was found for the battery electric drivetrain using hydroelectricity. The next two lowest carbon options were the series hybrid gas turbine drivetrain using landfill natural gas and the series hybrid fuel cell drivetrain using hydrogen from hydroelectricity. With a carbon-intensive electricity mix, the battery electric drivetrain was still found as the lowest GHG emissions option. On average after conventional diesel, parallel-hybrid diesel, parallel-hybrid compressed natural gas (CNG), as well as conventional CNG were found as drivetrains with the lowest total ownership cost per km. Overall, pure battery electric drivetrains were found to be most effective in GHG reductions under favorable conditions, but considering sensitivities to infrastructure costs, electricity carbon intensity and battery pack mass highlighted the effectiveness of parallel-hybrid diesel and conventional landfill based CNG drivetrains in certain scenarios.

This paper was sponsored by TRB committee ADC20 Standing Committee on Transportation and Air Quality.

19-01729

English

8p

2019

Transportation Research Board 98th Annual Meeting

Digital/other

Figures; References

Greenhouse gases; Heavy duty trucks; Monte Carlo method; Operating costs; Power trains

British Columbia

Energy; Environment; Freight Transportation; Vehicles and Equipment

Transportation Research Board Annual Meeting 2019 Paper #19-01729

TRIS, TRB, ATRI

Dec 7 2018 9:45AM