Model predictive engine torque control with real-time driver-in-the-loop simulation results

Abstract

This paper presents the design and simulation results for a novel off-idle engine torque control strategy that uses online model predictive control (MPC) to simultaneously manage drivability, emissions, and fuel economy, while delivering desired engine torque. In order to achieve a tractable optimization, a modular control approach is used, wherein MPC is used to manipulate desired air/fuel ratio, engine air charge, spark advance, and variable valve timing, whereas lower level controllers are designed using conventional design techniques to deliver these desired values. The performance of the proposed control strategy is exhibited through simulation results on two test cases, including a driver-in-the-loop simulator. Results show that the model predictive torque control strategy yields a significant overall improvement in terms of a combined drivability, emissions, and fuel economy metric.