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Energy Consumption Simulation for Connected and Automated Vehicles: Eco-driving Benefits versus Automation Loads
- Xiaoyi He - University of Michigan, Center for Sustainable Systems, School for Environment and Sustainability, USA ,
- Hyung Chul Kim - Ford Motor Company, Research & Advanced Engineering, USA ,
- Ruoyun Ma - Tsinghua University, School of Environment, and State Key Joint Laboratory of Environment Simulation and Pollution Control, China ,
- Timothy J. Wallington - Ford Motor Company, Research & Advanced Engineering, USA ,
- Gregory A. Keoleian - University of Michigan, Center for Sustainable Systems, School for Environment and Sustainability, USA ,
- Robert De Kleine - Ford Motor Company, Research & Advanced Engineering, USA ,
- Shaojun Zhang - Tsinghua University, School of Environment, and State Key Joint Laboratory of Environment Simulation and Pollution Control, China ,
- Ye Wu - Tsinghua University, School of Environment, and State Key Joint Laboratory of Environment Simulation and Pollution Control, China
Journal Article
12-06-01-0002
ISSN: 2574-0741, e-ISSN: 2574-075X
Sector:
Topic:
Citation:
He, X., Kim, H., Ma, R., Wallington, T. et al., "Energy Consumption Simulation for Connected and Automated Vehicles: Eco-driving Benefits versus Automation Loads," SAE Intl. J CAV 6(1):5-18, 2023, https://doi.org/10.4271/12-06-01-0002.
Language:
English
Abstract:
Eco-driving benefits and automation energy use
burdens are important factors impacting the energy
consumption of connected and automated vehicles (CAVs). However, challenges
exist in evaluating the balance between these benefits and burdens under
real-world driving conditions. Here we used a large dataset of 8064 real-world
trips to establish analytical relationships between driving characteristics and
fuel consumption for CAV sedans and sport utility vehicles (SUVs) with gasoline
and battery electric powertrains. The regression-based model enables rapid
estimation of eco-driving benefits using trip-level information (average speed
and aggressiveness factor) with an accuracy similar to computationally intensive
tools using second-by-second speed profiles. Three simulated scenarios
reflecting different levels of smooth driving and avoidance of low-speed driving
were considered. In the medium-level scenario, eco-driving reduces energy
consumption by a median of 17% for gasoline vehicles and by 14% for battery
electric vehicles (BEVs). Eco-driving benefits are more significant for trips
with lower average speeds. Automation power consumption below approximately 1000
W is needed for eco-driving benefits to outweigh automation burdens. For trips
with average speeds >60 km/h, even CAVs with an automation power consumption
of 2000 W have fuel economies similar to non-automated vehicles.