Fuel Efficient Control Algorithms for Connected and Automated Line-Haul Trucks

Abstract

In this paper, an optimal and predictive multilevel control solution is developed to utilize data and capabilities provided by the Connected and Automated Vehicle (CAV) technologies to reduce fuel consumption for line-haul class 8 trucks. The longer horizon road grade and speed limit data combined with shorter horizon and time-varying traffic data on real-world driving scenarios is utilized in the developed integrated optimal control algorithms to further reduce fuel consumption with respect to a production baseline control with state-of-art Advanced Driver-Assistance Systems (ADAS) control features. Furthermore, integration of the developed control algorithms for the front vehicle automation in platoon with a rear truck is also studied. The results indicate that with the application of the developed control solutions for powertrain efficiency in both single truck automation or the automation of the front truck in platoon with a rear truck, the fuel consumption is significantly reduced over real-world driving scenarios with road grade, speed limit and traffic data. The proposed solution is implementable in real-time with the utilization of CAV technologies with the proposed multilevel control architecture.