Robust physical quantities estimation for diesel engine emission reduction using sensor fusion

Abstract

Lowering heavy-duty emission thresholds towards ultra-low emission transportation systems constitute a seri-ous challenge. Indeed, the engine and exhaust aftertreatment systems have been complexified for decades to fulfill always stricter regulations. As a result, the powertrain represents a significant part of the final vehicle price. Therefore, advanced control methods are required to meet the upcoming emission thresholds without drastically increasing the system cost and complexity. Such control designs have already shown promising results but require accurate physical estimates - particularly the oxygen content in the intake and the exhaust manifold are essential information for a precise engine and aftertreatment systems control. Although observer methods exist for such accurate and robust estimations, they are not suitable for hardware implementation due to their complexity. This paper introduces an observer to estimate oxygen content-related physical signals. The proposed method takes advantage of all existing sensors and a simple dynamic model within a sensor fusion framework. The observer is implemented in an advanced simulation platform, where the observer estimates are shown to be unbiased and robust to noise and sensor inaccuracies. These results suggest that an advanced controller combined with the proposed observer method could reduce the engine-out transient emissions without supplementary hardware cost or complexity.