Ohio State Researchers Participate in Nation-Wide Effort to Reduce Vehicle Fuel Consumption of Heavy Duty Trucks by Twenty Percent
A new team of researchers at The Ohio State University are part of a nation-wide collaborative research effort to use connected and autonomous vehicle technologies to reduce a vehicles fuel consumption by 20 percent.
Stephanie Stockar, PhD, an assistant professor in the Department of Mechanical and Aerospace Engineering has brought her research and research group to The Ohio State University from Pennsylvania State University. Stockar and her team are part of a collaborative effort that aims to reduce the fuel consumption of semi-trucks by 20 percent.
“We are assuming that connected and autonomous vehicles have been established and that there is an exchange of information between vehicles on the road and infrastructure like traffic lights. We use that information to control the vehicle intelligently to save fuel,” said Stephen Boyle a graduate student in the Department of Mechanical and Aerospace Engineering, who came with Stockar to Ohio State.
This project is a multi-institutional endeavor lead by Penn State and involving Volvo Trucks North America, and students and faculty at Penn State, University of Maryland, Clemson, University of North Carolina and now, Ohio State.
The control structure consists of four layers, each developed by different institutions. Each layer performs its calculations and passes that information down to the subsequent layers. The first layer is the routing layer, that selects the route for the vehicle to follow by avoiding features that would increase fuel consumption, like high traffic areas or hills. The second layer is speed trajectory optimization, which optimizes vehicle velocity based on terrain and traffic light timing. The third layer is transmission control, which selects the most fuel-efficient gear. Finally, the fourth layer, engine and accessory control, is the focus of Stockar’s team’s research.
“The control hierarchy is structured by different layers- as a four-layer hierarchical control structure. The higher layers have been developed by other members of the team at other institutions and they provide a command profile that the engine should follow, but because of assumptions made by those layers, the engine is not able to do it exactly. My algorithm processes the desired control profile and translates it into something that the engine is capable of achieving without violating any constraints,” Boyle said. “For example, one problem is emissions. A rapid increase in the requested engine torque is met by instantaneously increasing the fueling rate. In a Diesel engine this will result in a sub-optimal combustion process, that will lead to increased engine emissions. Another problem is driver comfort, if you command too much torque too quickly the vehicle will accelerate sharply resulting in poor drivability.”
As part of the accessory control, Dr. Stockar’s team is currently focusing on the engine cooling optimization. This is motived by the use of vehicle platooning, a strategy in which you have vehicles driving in a line together, that reduces aerodynamic drag on the vehicles, which will help save on fuel consumption.
“The vehicle spacing required to achieve this benefit would be unsafe for human drivers to maintain, but autonomous vehicles in communication with each other can react more quickly, and remain safe at close following distances. But, when the vehicles are so close together, you block the air flow from the radiator, which could result in higher engine temperatures. Our engine cooling algorithm helps keep the engine cool, while minimizing the extra load the cooling fan puts on the engine.” said Brian Block, a graduate student in the Department of Mechanical and Aerospace Engineering, who worked with Stockar during his undergraduate studies at Penn State, and is now continuing his work in the PhD program here at Ohio State.
Currently the team is conducting engine-in-the loop testing. An engine on a dynamometer at Volvos test facility is being used to test their algorithms. While the vehicle dynamics are being simulated, the team is able to see exactly how a real engine reacts to their control strategies, and experimentally quantify their economy claims.
The layer that Stockar’s team is working on will save 2 to 3 percent on fuel consumption. While that number may not seem like a lot, for large shipping companies, it could equate to millions of dollars in savings. By integrating these strategies in the hierarchy, the team is projected to meet their 20 percent goal.
Written by Muhammed Al Refai, CAR Marketing and Communications Intern