INDUSTRY AT A GLANCE

Forward-thinking automakers and automotive suppliers know how critical it is to secure greater fuel economy.

Meeting global mandates will require implementing advanced combustion technologies, from Miller-cycle engines to electrification and autonomous technologies.

Only a few years ago, self-driving cars were considered science-fiction.

Today, autonomous cars are a rapidly evolving technology. These vehicles are designed to be wirelessly connected to each other and the cloud infrastructure, providing the engine controller actionable information about vehicle position, traffic, terrain, obstacles, traffic light changes, and more.

What is aDSF?

aDSF will be able to incorporate real-time and predicted data to deliver engine torque at maximum fuel efficiency.

Key solution components include:

Autonomous Infrastructure information: Information including vehicle position, traffic, terrain, obstacles, traffic light changes, plus any driver override requests
DSF valvetrain: Individual deactivation capability

Engine controller with aDSF: Tula’s proprietary aDSF SW integrates available autonomous information to calculate both real-time and anticipated torque demands at the most fuel-efficient operating points

How DSF^® works in tandem with Autonomous

How DSF works in tandem with autonomous

The blue curve in the graph illustrates a typical drive cycle of rapid accelerations, slowdowns, breaking and stops. The green curve is for an autonomous vehicle that anticipates traffic signals and other obstacles.

aDSF optimizes the fuel efficiency across the drive cycle, as steady operating conditions enable maximum DSF benefits. (In contrast to a human driver, aDSF can maintain speed precisely and un-emotionally).

aDSF will integrate autonomous torque requests with optimal engine operation feedback for passenger comfort and fuel economy.

When the vehicle is operated without a driver, aDSF is uniquely capable of relaxing Noise and Vibration (N&V) skip fire restrictions to further boost fuel efficiencies.

Press Releases

Determining the optimal strategy with reasonable assumptions is the subject of joint work between Tula, Delphi and OSU and is funded by ARPA-E. See the press releases below for more information.

Department of Energy funding to accelerate research on vehicle efficiency, optimization

Read Online

Fuel Economy Optimization with Dynamic Skip Fire in a Connected Vehicle