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Rebound effects from speed and acceleration in electric and internal combustion engine cars: An empirical and conceptual investigation

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  • Galvin, Ray

Abstract

Rebound effect studies of road vehicle travel focus mostly on increases in distance traveled after increases in energy efficiency. Average journeying speed also increases with energy efficiency, but rebound studies avoid quantifying speed-related rebound effects. This may underestimate rebound effects by around 60%. This study offers a first attempt to show how increases in speed and acceleration contribute to rebound effects, and how these can be quantified. Its empirical data is dynamometer test results for a plug-in electric car and an internal combustion engine (ICE) pick-up van with automatic transmission, each on the WLTP and NEDC drive cycles, representing driving styles from today and 1975 respectively. Rebound effects are estimated by comparing the WLTP and NEDC results, using typical 1975 energy efficiencies for the NEDC. The electric car shows a 20.5% speed rebound effect, and a mathematical development sets out how speed rebound effects can be included in traditional rebound effect analyses. Results for the ICE-vehicle do not allow a direct rebound effect estimate due to wasteful engine revving on the NEDC and wrong gear ratios for sedate travel. However, this can be seen as a form of ‘transformational’ rebound effect, where vehicle design locks drivers into fast driving styles.

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  • Galvin, Ray, 2016. "Rebound effects from speed and acceleration in electric and internal combustion engine cars: An empirical and conceptual investigation," Applied Energy, Elsevier, vol. 172(C), pages 207-216.
    • Handle: RePEc:eee:appene:v:172:y:2016:i:c:p:207-216
    DOI: 10.1016/j.apenergy.2016.03.120
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    Cited by:

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    3. Jihye Byun & Sungjin Park & Kitae Jang, 2017. "Rebound Effect or Induced Demand? Analyzing the Compound Dual Effects on VMT in the U.S," Sustainability, MDPI, vol. 9(2), pages 1-10, February.
    4. Tsokolis, D. & Tsiakmakis, S. & Dimaratos, A. & Fontaras, G. & Pistikopoulos, P. & Ciuffo, B. & Samaras, Z., 2016. "Fuel consumption and CO2 emissions of passenger cars over the New Worldwide Harmonized Test Protocol," Applied Energy, Elsevier, vol. 179(C), pages 1152-1165.
    5. Zhao, Xiaolei & Li, Xuemei & Mao, Yumeng & Fang, Jianjun, 2025. "Electric vehicle adoption and the energy rebound effect in the transportation sector: evidence from China," Transport Policy, Elsevier, vol. 169(C), pages 227-241.
    6. Ruzzenenti, Franco & Basosi, Riccardo, 2017. "Modelling the rebound effect with network theory: An insight into the European freight transport sector," Energy, Elsevier, vol. 118(C), pages 272-283.
    7. Zha, Donglan & Chen, Qian & Wang, Lijun, 2022. "Exploring carbon rebound effects in Chinese households’ consumption: A simulation analysis based on a multi-regional input–output framework," Applied Energy, Elsevier, vol. 313(C).
    8. Safarzadeh, Soroush & Rasti-Barzoki, Morteza, 2019. "A game theoretic approach for pricing policies in a duopolistic supply chain considering energy productivity, industrial rebound effect, and government policies," Energy, Elsevier, vol. 167(C), pages 92-105.
    9. Galvin, Ray & Martulli, Alessandro & Ruzzenenti, Franco, 2021. "Does power curb energy efficiency? Evidence from two decades of European truck tests," Energy, Elsevier, vol. 232(C).
    10. Shao, Shuai & Guo, Longfei & Yu, Mingliang & Yang, Lili & Guan, Dabo, 2019. "Does the rebound effect matter in energy import-dependent mega-cities? Evidence from Shanghai (China)," Applied Energy, Elsevier, vol. 241(C), pages 212-228.

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