Integrated Power Management and Aftertreatment System Control for Hybrid Electric Vehicles with Road Grade Preview

Abstract

This paper presents a model-based and integrated strategy for hybrid electric vehicle (HEV) power management and aftertreatment control with preview information of road grade. The HEV power management has been well studied for decades to optimize vehicle fuel economy by properly determining the power split ratio between internal combustion engine and electric motor. Meanwhile, the HEV tailpipe emissions have also been decreased, thanks to the implementation of aftertreatment systems, of which selective catalytic reduction (SCR) systems have been widely equipped in ground vehicles powered by diesel engines to reduce NOx emissions. For SCR systems, major efforts are dedicated to design the efficient ammonia dosing strategies for removing NOx without generating excessive ammonia slip at the tailpipe. By coordinately controlling the HEV power management and aftertreatment systems, it is possible to achieve lower fuel consumption and emissions from tailpipe. In addition, the proposed control strategy incorporates the preview road grade information to calculate the optimal torque-split ratio and ammonia dosing amount such that the overall performance can be improved for the trip. The road grade impacts on vehicle fuel consumption and emissions are investigated in this paper. A model-based controller with an explicit consideration of road grade has been analytically developed and verified in simulation environment. The performance of the proposed controller is evaluated under US06 test cycle and comparison results are presented to demonstrate the effectiveness of the proposed design. Controller’s real-time implementation potential is also discussed in this paper.

Yao Ma

Assistant Professor

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