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Impact of driving characteristics on electric vehicle energy consumption and range
Open accessAbstract
This study investigates the impact of driver behaviour/driving-style on the energy consumption, state-of-charge (SOC) usage and range, of all-electric vehicles (EVs). Results from many driving cycles using a sole driver, along with those from a pre-defined ∼40 km route encompassing both urban and rural roads in Sheffield (UK) with various drivers, are given and analysed. The platform for the study is an all electric-drive Smart Fortwo ED, supplied using Zebra battery technology. Measurements of real-time quantities such as wheel speed and SOC over a number of driving trials show that energy consumption is significantly affected by driving style, and that through basic statistical analysis of acceleration profiles, for instance, a metric for assessing ‘good driving practice’ can be obtained. It is ultimately shown that the difference between driving in a moderate manner, and more aggressively, can make ∼30% difference in energy consumption – amounting to 30 g/km of CO2 (equivalent) over the driving duty considered in this case. The results also highlight the substantial savings that can be accrued by appropriate traffic management in congested areas, by allowing the driver to minimise periods of repeated acceleration/deceleration and allow longer periods of steady-speed motion. Although a pure EV platform is used to focus the study, ultimately the results are more widely applicable to plug-in hybrid counterparts.
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Cited by
Driving Style Recognition for Intelligent Vehicle Control and Advanced Driver Assistance: A Survey
Marina Martinez, C., Heucke, M., Wang, F.-Y., Gao, B., & Cao, D. (2018) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2017.2706978 · Cited by 620
Energy consumption analysis and prediction of electric vehicles based on real-world driving data
Zhang, J., Wang, Z., Liu, P., & Zhang, Z. (2020) · Applied Energy · doi:10.1016/j.apenergy.2020.115408 · Cited by 322
Potential for widespread electrification of personal vehicle travel in the United States
Needell, Z. A., McNerney, J., Chang, M. T., & Trancik, J. E. (2016) · Nature Energy · doi:10.1038/nenergy.2016.112 · Cited by 287
Driving Style Classification Using a Semisupervised Support Vector Machine
Wang, W., Xi, J., Chong, A., & Li, L. (2017) · IEEE Transactions on Human-Machine Systems · doi:10.1109/thms.2017.2736948 · Cited by 265
Quantitative Driving Style Estimation for Energy-Oriented Applications in Road Vehicles
Corti, A., Ongini, C., Tanelli, M., & Savaresi, S. M. (2013) · 2013 IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/smc.2013.632 · Cited by 32
Metadata
- Authors
- Bingham, C., Walsh, C., & Carroll, S.
- Venue
- IET Intelligent Transport Systems
- Published
- 2012-03
- Volume
- 6
- Issue
- 1
- Pages
- 29-35
- ISSN
- 1751-956X (ISSN-L)
- 1751-9578
- OpenAlex
- W2151126419
- Cited by
- 211
- References
- 0
- FWCI
- 13.29
- Type
- journal article
- Language
- en
- Open access
- green
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- Bingham, C., Walsh, C., & Carroll, S. (2012). Impact of driving characteristics on electric vehicle energy consumption and range. IET Intelligent Transport Systems. https://doi.org/10.1049/iet-its.2010.0137
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