Researcher develops efficient powertrain controller for autonomous vehicle

Punit Tulpule, along with a team of faculty, researchers and staff at The Ohio State University’s Center for Automotive Research (CAR) is developing a powertrain controller for an autonomous and connected vehicle that could be 20 percent more efficient than a conventional vehicle.

The NEXTCAR project’s goal is to develop an autonomous vehicle that improves fuel economy. In addition to SAE Level 3 autonomous technology, the vehicle uses connected technology, allowing it to communicate with infrastructure and other vehicles. For example, it knows when traffic lights will turn green or where traffic is heavy, and it will adjust its speed or route accordingly. This means that the vehicle spends less time stopped in traffic, which would waste valuable energy while idling.

Tulpule’s task on the NEXTCAR project is to develop a real-time implementable hybrid-electric powertrain controller that is optimized for this new way of driving. By utilizing connected features to learn what is happening later in the route, the vehicle’s controller can determine how much power should be drawn from the gasoline engine and electric motor to achieve maximum efficiency.

“Autonomous vehicles have access to information further down the road,” Tulpule said. “This future information is called look-ahead information, and the question we are trying to answer is, ‘How can we use the look-ahead information to improve powertrain performance?’”

The NEXTCAR team used globally optimal look-ahead control methods to optimize the powertrain operations. To improve cost efficiency, Tulpule, who also works at Ohio State’s Simulation, Innovation and Modeling Center (SIMCenter), developed a computer program to reduce the computation time by orders of magnitude. This will be the first time this method has been demonstrated on a vehicle.

NEXTCAR is sponsored by the Department of Energy (DOE) and the Advanced Research Projects Agency-Energy (ARPA-E). Partners include The Ohio State University, the Transportation Research Center (TRC), Delphi Technologies, Aptiv and Tula Technology.

Written by Jake Berg, CAR Writing Intern