Modern drivers are skilled at anticipating and reacting to the behavior of nearby vehicles and the environment in order to travel safely. Nevertheless, all drivers operate with an information gap – a level of uncertainty that limits vehicle energy efficiency. For instance, safe driving demands that drivers leave appropriate space between vehicles and cautiously approach intersections, because one can never fully know the intentions of nearby vehicles or yet unseen traffic conditions. Closing this information gap can enable vehicles to operate in more energy efficient ways. The increased development of connected and automated vehicle systems, currently used mostly for safety and driver convenience, presents new opportunities to improve the energy efficiency of individual vehicles. Onboard sensing and external connectivity using Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), and Vehicle-to-Everything (V2X) technologies will allow a vehicle to “know” its future operating environment with some degree of certainty, greatly narrowing previous information gaps. By providing the ability to predict driving conditions, these technologies could operate the vehicle powertrain (including the engine, transmission, and other components) more intelligently, generating significant vehicle energy savings.
Project Innovation + Advantages:
The University of Minnesota (UMN) will lead a team to develop technology to improve the fuel efficiency of delivery vehicles through real-time vehicle dynamic and powertrain control optimization using two-way vehicle-to-cloud (V2C) connectivity. The effort will lead to greater than 20% fuel economy improvement of a baseline 2016 E-GEN series hybrid delivery vehicle operating as part of the United Parcel Service (UPS) fleet. Large delivery vehicle fleet operators such as UPS currently use analytics to assign routes in such a way to minimize fuel consumption. Algorithms mine historical data collected from vehicles to determine routes before a driver leaves a distribution center. UPS has also invested in E-GEN series electric-powertrain vehicles that allow pure electric driving for extended periods of time and use a small range-extending gasoline engine-generator to charge the battery, allowing routes longer than 550 miles. However, the current UPS routing algorithms do not interact with the vehicle directly to improve the fuel economy in real-time. The UMN project will integrate the E-GEN vehicles with real-time powertrain optimization and two-way V2C connectivity. The vehicle's powertrain controller will be pre-programmed at the beginning of a route to optimize efficiency using historical data and known parameters like terrain, weather, and traffic. Powertrain calibration will be optimized and downloaded to the vehicle using V2C connectivity in real-time during a delivery route, compensating for parameter changes or unpredicted driver behavior. The team's technology may also be commercialized far quicker because UPS, in particular, already uses E-GEN vehicles. Large delivery fleet operators, more broadly, are also heavily invested in data collection for reducing fuel consumption and actively track their vehicles, both factors that could potentially accelerate deployment.
If successful, developments made from the UMN project will enable at least an additional 20% reduction in energy consumption of future connected and automated delivery vehicles.
Project innovations could lead to a dramatically more efficient domestic vehicle fleet, lessening U.S. dependence on imported oil.
Greater efficiency in transportation can help reduce sector emissions, helping improve urban air quality and decreasing the sector’s carbon footprint.
Project innovations would further solidify the United States’ status as a global leader in connected and automated vehicle technology, while a more efficient vehicle fleet would reduce energy cost per mile driven and bolster economic competitiveness.