Fuel Economy Optimization of HDVs Using CV Technologies
Clinical Professor of Engineering Practice, College of Engineering
Associate Professor of Mechanical Engineering and Associate Professor of Civil and Environmental Engineering, College of Engineering
The research objective of this proposal was to establish new ways of improving the fuel economy of trucks by exploiting connected-vehicle (CV) technologies. Instead of focusing on redesigning the engine characteristics, our tools relied on optimal use of real-time information available through dedicated short range communications. We used vehicle-to-vehicle communication in order to map the neighborhoods of the heavy-duty vehicles (HDVs) within a few hundred meters and used network-based optimization techniques to use this information in an optimal way.
Connected cruise control algorithms that utilize velocity from multiple vehicles ahead, leading to significant fuel economy improvements while also attenuating congestion waves.