Towards Optimal Real-Time Automotive Emission Control

Abstract: The legal bounds on both toxic and carbon dioxide emissions from automotive vehicles are continuously being lowered, forcing manufacturers to rely on increasingly advanced methods to reduce emissions and improve fuel efficiency. Though great strides have been made to date, there is still a large potential for continued improvement. Today, many subsystems in vehicles are optimized for static operation, where subsystems in the vehicle perform well at constant operating points. Extending optimal operation to the dynamic case through the use of optimal control is one method for further improvements. This thesis focuses on two subtopics that are crucial for implementing optimal control; dynamic modeling of vehicle subsystems, and methods for generating and evaluating computationally efficient optimal controllers. Though today's vehicles are outfitted with increasingly powerful computers, their computational performance is low compared to a conventional PC. Any controller must therefore be very computationally efficient in order to feasibly be implemented. Furthermore, a sufficiently accurate dynamic model of the subsystem is needed in order to determine the optimal control value. Though many dynamic models of the vehicle's subsystems exist, most do not fulfill the specific requirements set by optimal controllers. This thesis comprises five papers that, together, probe some methods of implementing dynamic optimal control in real-time. Two papers develop optimal control methods, one introduces and studies a cold-start model of the three-way catalyst, one paper extends the three-way catalyst model and studies optimal cold-start control, and one considers fuel-optimally controlling the speed of the engine in a series-hybrid. By combining the method and model papers we open for the potential to reduce toxic emissions by better managing cold-starts in hybrid vehicles, as well as reducing carbon dioxide emissions by operating the engine in a more efficient manner during transients.