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Quantifying the Economic Case for Electric Semi-Trucks

Shashank Sripad, Venkatasubramanian Viswanathan

arXiv 16 Apr 2018 · Econometrics

arXiv:1804.05974 · PDF · DOI · OpenAlex · Extracted main text

Abstract

There has been considerable interest in the electrification of freight transport, particularly heavy-duty trucks to downscale the greenhouse-gas (GHG) emissions from the transportation sector. However, the economic competitiveness of electric semi-trucks is uncertain as there are substantial additional initial costs associated with the large battery packs required. In this work, we analyze the trade-off between the initial investment and the operating cost for realistic usage scenarios to compare a fleet of electric semi-trucks with a range of 500 miles with a fleet of diesel trucks. For the baseline case with 30% of fleet requiring battery pack replacements and a price differential of US$50,000, we find a payback period of about 3 years. Based on sensitivity analysis, we find that the fraction of the fleet that requires battery pack replacements is a major factor. For the case with 100% replacement fraction, the payback period could be as high as 5-6 years. We identify the price of electricity as the second most important variable, where a price of US$0.14/kWh, the payback period could go up to 5 years. Electric semi-trucks are expected to lead to savings due to reduced repairs and magnitude of these savings could play a crucial role in the payback period as well. With increased penetration of autonomous vehicles, the annual mileage of semi-trucks could substantially increase and this heavily sways in favor of electric semi-trucks, bringing down the payback period to around 2 years at an annual mileage of 120,000 miles. There is an undeniable economic case for electric semi-trucks and developing battery packs with longer cycle life and higher specific energy would make this case even stronger.

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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
nrcreportunmatched citation key nrcreport1.00094100%
atri2017unmatched citation key atri20171.00084100%
davis2017transportationunmatched citation key davis2017transportation1.00073100%
nptcreportunmatched citation key nptcreport0.92843100%
sripad2017performanceunmatched citation key sripad2017performance0.92843100%
eia2018aeounmatched citation key eia2018aeo0.87462100%
icct_supertunmatched citation key icct_supert0.84333100%
bnefunmatched citation key bnef0.81142100%
eia2018electricunmatched citation key eia2018electric0.73732100%
eiadieselunmatched citation key eiadiesel0.73732100%

Showing the top 10 of 34 scored citations. 10 of these could not be matched to a bibliography entry, so only the citation key is shown.