Model Based Control of Automotive Selective Catalytic Reduction Systems with Road Grade Preview


This paper introduces a model-based control method for automotive selective catalytic reduction (SCR) systems with preview information of road grade. SCR systems have been widely adopted in Diesel powered ground vehicles to reduce tailpipe NO x emissions. The major control problem is to properly design the ammonia dosing strategy that can efficiently remove NO x without generating excessive NH 3 slip at the tailpipe. While most existing methods only utilize sensor feedback information to design controllers, the SCR controller performance can be improved by incorporating preview of road information such that the controller can act in a proactive fashion and reduce emissions over the whole trip. Road grade impact on vehicle SCR system is investigated in this paper. A corresponding controller with explicit consideration of preview road grade is developed and verified in a simulation environment. Comparison results under the US06 test cycle are presented to demonstrate the efficiency improvement of the proposed controller.

In Proceedings of the 2018 American Control Conference
Yao Ma
Assistant Professor

My research interests focus on control and modeling of intelligent vehicle systems for improvement of efficiency, mobility, and safety.