Synergistic and intelligent control of vehicle powertrain-aftertreatment systems

This study aims to investigate the potential improvement of energy efficiency and emission performance for a ground transportation system equipped with connected and automated vehicles (CAV) by means of intelligent and coordinated control design from vehicle powertrain and aftertreatment perspectives. First, a dedicated control algorithm is designed for heavy-duty vehicle exhaust emission aftertreatment system against unknown catalyst aging condition. To reduce the tailpipe NO[subscript x] emissions, urea-based selective catalytic reduction (SCR) systems, which utilize ammonia as the reducing agent for deNO[subscript x] reactions, have become indispensable for Diesel engine powertrains in ground vehicles. A closed-loop cost-friendly SCR controller is designed for the implementation purpose. Second, predictive control methods for vehicle powertrain and aftertreatment systems utilizing information induced by road environment perception and connectivity of vehicles are proposed. Simulation results indicate the overall emission performance as well as energy efficiency can be improved with a proper synthesis of preview information and coordinated control design. Third, the impacts of human driver behaviors variation on vehicle fleet energy consumption and travel time are evaluated providing insights on future CAV control design for efficiency improvement. Through a proper integration of these three interconnected aspects, an energy-efficient mobility for future transportation system is envisioned