Driving Research into Improved Tractor-Trailer Fuel Efficiency

Engineering students at Purdue will soon be participating in a national effort to reduce vehicle fuel consumption by 20 percent, which involves creating automated systems that interconnect vehicles with transportation infrastructure via sensors and online cloud technology.

The project is one of ten being funded by $32 million in grants from the U.S. Department of Energy’s Advanced Research Projects Agency-Energy’s Next-Generation Energy Technologies for Connected and Autonomous On-Road Vehicles (NEXTCAR) program.

Four engineering graduate students at Purdue University will participate in a $5 million, three-year project that focuses on Class 8 trucks, or tractor-trailers. They’ll be working alongside team members from companies and groups such as Cummins Inc., Peloton Technology, Peterbilt Motors Co., the National Renewable Energy Laboratory (NREL) and ZF TRW to explore concepts to improve fuel efficiency in this class of trucks.

Purdue doctoral student Dheeraj Gosala, foreground, works on an engine. Looking on is Gregory Shaver, a Purdue professor of mechanical engineering who is leading part of a national effort to reduce vehicle fuel consumption by 20 percent. The research is funded through the U.S. Department of Energy’s Advanced Research Projects Agency-Energy. (Image courtesy of Purdue University/Charles Jischke.)

The students and researchers will explore three concepts over the course of the project:

  • On-the-fly recalibration of the engines and transmissions that allow constant adaptation to new driving conditions
  • Running-model-based algorithms that sync with online information in the cloud as the vehicle drives
  • Platooning with enhanced capabilities, such as synchronizing transmission shifting between two trucks.                                                                                                                                                                                                                                             The student project team’s final goal will be enabling these trucks to tap into forward-looking information that shows changes in road, traffic and driving conditions several miles ahead. Each truck will also be connected to a cloud-based network operations center that gives access to information from crowd-sourced traffic data, road grade maps and weather services.“These vehicles will be driven as if every driver had forward-looking information about what’s happening a few miles down the road, what the grades are going to be, where the hills are going to be, what the vehicle in front of them is doing,” said Gregory Shaver, the Purdue professor of mechanical engineering who is leading the team. “They are going to be able to react much more quickly, and safely, than a human driver could.”The platooning algorithms will work to position the trucks together in groups so they can reduce wind drag and cut fuel consumption.

    “It’s also the same thing that happens when you have a cluster of bicycles, called a peloton, in competitive racing,” explained Shaver “They come together like that because together they reduce the drag on each other. Through automation, we want to get the trucks closer together than human drivers could safely drive them, and we can do this because the connectivity and algorithms are inherently faster, and more accurate, than humans.”

    While the new technologies will be designed to work both on highways and in cities, the emphasis is on highway conditions because that’s where the Class 8 trucks rack up the most mileage, Shaver added.

    The end goal for the engineering students and their research team is to demonstrate the technology by the end of the three-year project. They’ll also be working under the requirement of keeping the commercial cost of the technology under $3,000 – and thus allowing for a market pathway toward improving the fuel and energy efficiency of transport trucks.                                                                                                               Source: http://www.engineering.com/