Journal
NATURE ENERGY
Volume 5, Issue 7, Pages 543-549Publisher
NATURE PUBLISHING GROUP
DOI: 10.1038/s41560-020-0644-3
Keywords
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Funding
- Carnegie Mellon University (CMU) College of Engineering, Department of Engineering and Public Policy
- Scott Institute for Energy Innovation
- National Science Foundation [SES-1463492]
- CMU [SES-1463492]
- Block Center for Technology and Society at CMU
- Technologies for Safe and Efficient Transportation University Transportation Center
- Mobility21, A United States Department of Transportation National University Transportation Center
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Weight, computing load, sensor load and possibly higher drag may increase the energy use of automated electric vehicles relative to human-driven electric vehicles, although this increase may be offset by smoother driving. Here, we use a vehicle dynamics model to evaluate the trade-off between automation and electric vehicle range and battery longevity. We find that automation will likely reduce electric vehicle range by 5-10% for suburban driving and by 10-15% for city driving. The effect on range is strongly influenced by sensor drag for suburban driving and computing loads for city driving. The impact of automation on battery longevity is negligible. While some commentators have suggested that the power and energy requirements of automation mean that the first automated vehicles will be gas-electric hybrids, our results suggest that this need not be the case if automakers can implement energy-efficient computing and aerodynamic sensor stacks. Autonomous driving is being implemented in electric vehicles, but its energy impact is unclear. Here the authors build physics models to analyse the energy demand of autonomous electric vehicles and suggest that the influences of automation on vehicle range and battery longevity are small.
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