Predictive Data-Driven Automotive Control

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Berkeley, California
Project Term:
03/03/2017 - 12/31/2024

Technology Description:

The University of California, Berkeley (UC Berkeley) team has developed an innovative vehicle dynamics and powertrain (VD&PT) control architecture based on a predictive and data-driven approach. In the NEXTCAR program, UC Berkeley optimized the performance of a plug-in hybrid electric vehicle (PHEV) in real-world conditions, improving efficiency up to 30% in urban driving and 14% on the highway. In the next NEXTCAR phase, UC Berkeley will adapt and expand its eco-route, eco-drive, and eco-charge controls to leverage connectivity and SAE (Society of Automotive Engineers) Level 4 (L4) automation to generate additional fuel efficiency benefits in electrified vehicles including EVs and PHEVs. UC Berkeley’s NEXTCAR project resulted in a spin-off company, WideSense Inc., which will commercialize the technologies developed in both phases of the project.

Potential Impact:

If successful, UC Berkeley’s project will enable at least an additional 20% reduction in energy consumption of future connected and automated vehicles.


These 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.


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.


ARPA-E Program Director:
Dr. Priyanka Bakaya
Project Contact:
Prof. Francesco Borrelli
Press and General Inquiries Email:
Project Contact Email:


Hyundai America Technical Center
Sensys Networks

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