NREL and Volvo partner to demonstrate approach to quantify Automated Vehicle fuel savings

Automated control of cars may enable drivers to rack up more fuel savings than if they were completely in charge, according to a new study conducted by the U.S. Department of Energy’s National Renewable Energy Laboratory (NREL) and Volvo Cars.

Placing a number on the fuel efficiency of such vehicles is challenging, as fuel economy is typically measured in a laboratory setting, but that doesn’t work for automated vehicles. This challenge motivated NREL to develop an objective approach for quantifying real-world efficiency impacts from automated vehicle technologies.

NREL partnered with Volvo Cars to demonstrate the approach. The researchers leveraged on-road data from Volvo vehicles driving around Gothenburg, Sweden, and compared fuel efficiency for cars that used adaptive cruise control (ACC) to those that did not. ACC is a partial automation technology that relies on cameras and radar sensors in a vehicle to set its speed and distance from the car in front.

The car manufacturer supplied data from more than 18,500 trips taken by employees and their family members operating similar Volvo vehicles within the designated analysis area.

The fuel economy calculation approach quantifies vehicle fuel efficiency in a wide variety of driving conditions both when ACC is active and when it is inactive. It then weights each condition-specific fuel efficiency by the amount of driving that occurs in each condition to obtain the overall fuel economy for manual vs. ACC operation.

Following this procedure, the researchers found the use of ACC resulted in a 5%-7% drop in those vehicles’ fuel consumption.

With automated vehicles possessing enhanced data collection and connectivity capabilities, this approach could further provide visibility into how on-road fuel economy evolves with changes in vehicle technology, penetration rates, and traffic impacts.

The study findings are detailed in the paper “An Automated Vehicle Fuel Economy Benefits Framework Using Real-World Travel and Traffic Data

Source: Press Release


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