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Potential for widespread electrification of personal vehicle travel in the United States

Abstract

Electric vehicles can contribute to climate change mitigation if coupled with decarbonized electricity, but only if vehicle range matches travellers’ needs. Evaluating electric vehicle range against a population’s needs is challenging because detailed driving behaviour must be taken into account. Here we develop a model to combine information from coarse-grained but expansive travel surveys with high-resolution GPS data to estimate the energy requirements of personal vehicle trips across the US. We find that the energy requirements of 87% of vehicle-days could be met by an existing, affordable electric vehicle. This percentage is markedly similar across diverse cities, even when per capita gasoline consumption differs significantly. We also find that for the highest-energy days, other vehicle technologies are likely to be needed even as batteries improve and charging infrastructure expands. Car sharing or other means to serve this small number of high-energy days could play an important role in the electrification and decarbonization of transportation.

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Figure 1: Energy intensities and velocity histories of trips with similar distances and durations.
Figure 2: Probabilistic model of BEV range given observed nationwide travel behaviour.
Figure 3: Nationwide and city-specific BEV energy requirements evaluated against battery capacity.
Figure 4: Vehicle-day energy distributions in various cities and the differentiating effect of their heavy tails.
Figure 5: Differences in travel behaviour and vehicle use across cities.
Figure 6: Effects of increasing battery capacity on BEV range constraints.

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References

  1. US Department of Energy, Energy Information Administration (EIA) Annual Energy Outlook with Projections to 2040 (2014).

  2. Federal Highway Administration 2009 National Household Travel Survey (US Department of Transportation, 2011).

  3. The White House, Office of the Press Secretary US–China Joint Announcement on Climate Change and Clean Energy Cooperation White House Fact Sheet (2014); http://www.whitehouse.gov/the-press-office/2014/11/11/fact-sheet-us-china-joint-announcement-climate-change-and-clean-energy-c

  4. Polzin, S. & Chu, X. Peak vehicle miles traveled and postpeak consequences? Transp. Res. Record 22–29 (2014).

  5. Sager, J., Apte, J. S., Lemoine, D. M. & Kammen, D. M. Reduce growth rate of light-duty vehicle travel to meet 2050 global climate goals. Environ. Res. Lett. 6, 024018 (2011).

    Article  Google Scholar 

  6. Sioshansi, R., Fagiani, R. & Marano, V. Cost and emissions impacts of plug-in hybrid vehicles on the Ohio power system. Energy Policy 38, 6703–6712 (2010).

    Article  Google Scholar 

  7. Donateo, T., Ingrosso, F., Licci, F. & Laforgia, D. A method to estimate the environmental impact of an electric city car during six months of testing in an Italian city. J. Power Sources 270, 487–498 (2014).

    Article  Google Scholar 

  8. Tamayao, M.-A. M., Michalek, J. J., Hendrickson, C. & Azevedo, I. M. Regional variability and uncertainty of electric vehicle life cycle CO2 emissions across the United States. Environ. Sci. Technol. 49, 8844–8855 (2015).

    Article  Google Scholar 

  9. Williams, J. H. et al. The technology path to deep greenhouse gas emissions cuts by 2050: the pivotal role of electricity. Science 335, 53–60 (2012).

    Article  Google Scholar 

  10. Kennedy, C., Ibrahim, N. & Hoornweg, D. Low-carbon infrastructure strategies for cities. Nature Clim. Change 4, 343–346 (2014).

    Article  Google Scholar 

  11. Traut, E., Hendrickson, C., Klampfl, E., Liu, Y. & Michalek, J. J. Optimal design and allocation of electrified vehicles and dedicated charging infrastructure for minimum life cycle greenhouse gas emissions and cost. Energy Policy 51, 524–534 (2012).

    Article  Google Scholar 

  12. Lipman, T. & Delucchi, M. A. Sustainable Transportation Energy Pathways Comparing Greenhouse Gas Emissions 133–170 (UC Davis Institute of Transportation Studies, 2011).

    Google Scholar 

  13. Tran, M., Banister, D., Bishop, J. D. K. & McCulloch, M. D. Realizing the electric-vehicle revolution. Nature Clim. Change 2, 328–333 (2012).

    Article  Google Scholar 

  14. Meinrenken, C. J. & Lackner, K. S. Fleet view of electrified transportation reveals smaller potential to reduce GHG emissions. Appl. Energy 138, 393–403 (2015).

    Article  Google Scholar 

  15. Kelly, J. C., MacDonald, J. S. & Keoleian, G. A. Time-dependent plug-in hybrid electric vehicle charging based on national driving patterns and demographics. Appl. Energy 94, 395–405 (2012).

    Article  Google Scholar 

  16. Green, R. C., Wang, L. & Alam, M. The impact of plug-in hybrid electric vehicles on distribution networks: a review and outlook. Renew. Sust. Energ. Rev. 15, 544–553 (2011).

    Article  Google Scholar 

  17. Peterson, S. B. & Michalek, J. J. Cost-effectiveness of plug-in hybrid electric vehicle battery capacity and charging infrastructure investment for reducing US gasoline consumption. Energy Policy 52, 429–438 (2013).

    Article  Google Scholar 

  18. Saber, A. Y. & Venayagamoorthy, G. K. Plug-in vehicles and renewable energy sources for cost and emission reductions. IEEE Trans. Ind. Electron. 58, 1229–1238 (2011).

    Article  Google Scholar 

  19. Birnie, D. P. Solar-to-vehicle (S2V) systems for powering commuters of the future. J. Power Sources 186, 539–542 (2009).

    Article  Google Scholar 

  20. Franke, T. & Krems, J. F. What drives range preferences in electric vehicle users? Transp. Policy 30, 56–62 (2013).

    Article  Google Scholar 

  21. Egbue, O. & Long, S. Barriers to widespread adoption of electric vehicles: an analysis of consumer attitudes and perceptions. Energy Policy 48, 717–729 (2012).

    Article  Google Scholar 

  22. Hidrue, M. K., Parsons, G. R., Kempton, W. & Gardner, M. P. Willingness to pay for electric vehicles and their attributes. Resour. Energy Econ. 33, 686–705 (2011).

    Article  Google Scholar 

  23. Khan, M. & Kockelman, K. M. Predicting the market potential of plug-in electric vehicles using multiday GPS data. Energy Policy 46, 225–233 (2012).

    Article  Google Scholar 

  24. Pearre, N. S., Kempton, W., Guensler, R. L. & Elango, V. V. Electric vehicles: How much range is required for a day’s driving? Transp. Res. C 19, 1171–1184 (2011).

    Article  Google Scholar 

  25. Vyas, A. D., Santini, D. J. & Johnson, L. R. Potential of plug-in hybrid electric vehicles to reduce petroleum use. Transp. Res. Record 55–63 (2009).

  26. Karabasoglu, O. & Michalek, J. Influence of driving patterns on life cycle cost and emissions of hybrid and plug-in electric vehicle powertrains. Energy Policy 60, 445–461 (2013).

    Article  Google Scholar 

  27. Yuksel, T. & Michalek, J. Effects of regional temperature on electric vehicle efficiency, range, and emissions in the United States. Environ. Sci. Technol. 49, 3974–3980 (2015).

    Article  Google Scholar 

  28. Newman, P. W. G. & Kenworthy, J. R. Gasoline consumption and cities. J. Am. Plan. Assoc. 55, 24–37 (1989).

    Article  Google Scholar 

  29. Cervero, R. & Murakami, J. Effects of built environments on vehicle miles traveled: evidence from 370 US urbanized areas. Environ. Plan. A 42, 400–418 (2010).

    Article  Google Scholar 

  30. Gately, C. K., Hutyra, L. R. & Sue Wing, I. Cities, traffic, and CO2: a multidecadal assessment of trends, drivers, and scaling relationships. Proc. Natl Acad. Sci. USA 112, 4999–5004 (2015).

    Article  Google Scholar 

  31. Miotti, M., Supran, G. J., Kim, E. J. & Trancik, J. E. Personal vehicle technologies evaluated against climate change mitigation targets. Environ. Sci. Technol.http://dx.doi.org/10.1021/acs.est.6b00177 (in the press).

  32. Wilcok, S. & Marion, W. Users Manual for TMY3 Data Sets NREL/TP-581-43156 (National Renewable Energy Laboratory, 2008).

  33. The Transportation Secure Data Center California Household Transportation Survey DOE-019-9889603959 (National Renewable Energy Laboratory, 2012).

  34. Fuel Economy Test Car List Database Files (US Environmental Protection Agency, 2015); http://www3.epa.gov/otaq/tcldata.htm

  35. Nissan 2013 Leaf Owner’s Manual (2013).

  36. Batteries for Electrical Energy Storage in Transportation (BEEST) (ARPA-E, United States Department of Energy, 2010); http://go.nature.com/2atP9xI

  37. Bingham, C., Walsh, C. & Carroll, S. Impact of driving characteristics on electric vehicle energy consumption and range. Intel. Trans. Syst., IET 6, 29–35 (2012).

    Article  Google Scholar 

  38. Raykin, L., Roorda, M. J. & MacLean, H. L. Impacts of driving patterns on tank-to-wheel energy use of plug-in hybrid electric vehicles. Transp. Res. D 17, 243–250 (2012).

    Article  Google Scholar 

  39. Li, H., Guensler, R. L., Ogle, J. H., Jun, J. & Elango, V. V. Transportation Research Board 86th Annual Meeting 07-1688 (2007).

  40. Bettencourt, L. M. The origins of scaling in cities. Science 340, 1438–1441 (2013).

    Article  MathSciNet  Google Scholar 

  41. Bettencourt, L. & West, G. A unified theory of urban living. Nature 467, 912–913 (2010).

    Article  Google Scholar 

  42. Argonne National Laboratory GREET 1 model (2014); https://greet.es.anl.gov

  43. Office of Highway Policy Information FHWA Forecasts of Vehicle Miles Traveled (VMT): May 2015 (Federal Highway Administration, 2015).

  44. Den Elzen, M. & Höhne, N. Reductions of greenhouse gas emissions in Annex I and non-Annex I countries for meeting concentration stabilization targets. Climatic Change 91, 249–274 (2008).

    Article  Google Scholar 

  45. Trancik, J. E., Chang, M. T., Karapataki, C. & Stokes, L. C. Effectiveness of a segmental approach to climate policy. Environ. Sci. Technol. 48, 27–35 (2014).

    Article  Google Scholar 

  46. SB-350, Clean Energy and Pollution Reduction Act of 2015 (California, 2015); https://leginfo.legislature.ca.gov/faces/billTextClient.xhtml?bill_id=201520160SB350

  47. Gil, A. & Taiber, J. Sustainable Automotive Technologies 2013 289–298 (Springer, 2014).

    Book  Google Scholar 

  48. Chen, T. D. Management of a Shared, Autonomous, Electric Vehicle Fleet: Vehicle Choice, Charging Infrastructure & Pricing Strategies PhD thesis, Univ. Texas at Austin (2015).

  49. Lutsey, N. A technical analysis of model year 2011 US automobile efficiency. Transp. Res. D 17, 361–369 (2012).

    Article  Google Scholar 

  50. 2013 American Community Survey 1-year estimate Table B01003 (United States Census Bureau, 2014).

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Acknowledgements

We thank M. Miotti for his contributions to the auxiliary power component of the TripEnergy model, and F. Riether for his contributions to characterizing the model robustness. We thank J. Heywood and S. Zoepf for their feedback on the vehicle model. We thank L. Chancel for a helpful discussion of transportation energy consumption in cities. This work was supported by the New England University Transportation Center at MIT under DOT grant No. DTRT13-G-UTC31, the MIT Leading Technology and Policy Initiative, the Singapore-MIT Alliance for Research and Technology, the Charles E. Reed Faculty Initiatives Fund, and the MIT Energy Initiative.

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Authors and Affiliations

Authors

Contributions

J.E.T. designed the study; J.M., M.T.C., Z.A.N. and J.E.T. built the model; Z.A.N., M.T.C., J.M. and J.E.T. performed the analysis; J.E.T., Z.A.N. and J.M. wrote the paper.

Corresponding author

Correspondence to Jessika E. Trancik.

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Competing interests

The authors declare no competing financial interests.

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Supplementary Information

Supplementary Figures 1–12, Supplementary Tables 1–5, Supplementary Notes 1–4, Supplementary References. (PDF 828 kb)

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Needell, Z., McNerney, J., Chang, M. et al. Potential for widespread electrification of personal vehicle travel in the United States. Nat Energy 1, 16112 (2016). https://doi.org/10.1038/nenergy.2016.112

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