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A team led by Southwest Research Institute (SwRI) has been awarded up to $2.9 million in funding to develop connected and automated vehicle (CAV) technologies aimed at improving fuel economy by more than 20 percent. The project is part of ARPA-E’s Next-Generation Energy Technologies for Connected and Autonomous On-Road Vehicles (NEXTCAR) program.
The three-year project, “Model Predictive Control for Energy-Efficient Maneuvering of Connected and Automated Vehicles,” calls for the team to develop optimal control algorithms that leverage vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and other vehicle-to- everything (V2X) technologies to simultaneously optimize the vehicle’s route, speed profile, and power flows from the hybrid system. These developments could help define future powertrain performance requirements and enable more efficient control of the powertrain and vehicle dynamics. SwRI will demonstrate these technologies using a plug-in hybrid electric vehicle (PHEV), Toyota’s 2017 Prius Prime.
“This is an important research step in furthering the development of powertrains for connected and automated vehicles,” said Scott Hotz, an assistant director in SwRI’s Engine, Emissions and Vehicle Research Division. “Our team’s collective expertise in vehicle powertrain development and connected and automated vehicle technologies will help optimize vehicle efficiency.”
The team will develop and integrate components that assist in automated eco-driving — informing the vehicle about approaching traffic signals as well as preferred routes and optimal vehicle speed profiles. Given this connected “look ahead” preview of conditions, SwRI engineers also will optimize powertrain operation to achieve its goal of 20 percent improvement in fuel economy.
In addition to SwRI, team members include Toyota Motor North America and the University of Michigan.
ARPA-E’s NEXTCAR (NEXT-Generation Energy Technologies for Connected and Automated On-Road Vehicles) Program supports “enabling technologies that use connectivity and automation to co-optimize vehicle dynamic controls and powertrain operation, thereby reducing the energy consumption of light-, medium- and heavy-duty vehicles.”