Thomas Alan Brewbaker

Multivariable diesel low-pressure EGR controller designed by input-output linearization

A multivariable low-pressure (LP) exhaust gas recirculation (EGR) controller that simultaneously regulates the LP-EGR mass flow rate and differential pressure using a LP-EGR valve and a LP-intake throttle was designed by input-output linearization plus proportional-integral (PI) control. The controller includes a PI limitation strategy that prioritizes tracking the flow-rate setpoint over the differential-pressure setpoint if either one of the two actuators saturates. A consequence of the limitation strategy is that setting the differential-pressure setpoint unachievably low, e.g. zero, forces the multivariable controller to operate as a single-input two-output (SITO) controller that tracks the LP-EGR flow-rate setpoint while using the LP-EGR valve and throttle as a single chained actuator. Two cases-one with the multivariable controller and a second with the SITO chained-actuator controller-were experimentally compared in a 6.7-liter diesel medium-duty truck. The multivariable controller achieved a lower 2-norm control error and required less actuator movement than the chained-actuator controller, while the chained-actuator controller minimized the differential pressure necessary to achieve the desired LP-EGR flow rate.

In-cylinder pressure sensor–based NOx model for real-time application in diesel engines

A real-time implementable, zero-dimensional model for predicting engine-out emissions of nitrogen oxides using in-cylinder pressure measurements is developed. The model is an extension of existing works in open literature that align well with the objectives of real-time implementation. The proposed model uses a simplified Zeldovich NOx mechanism that uses combustion-related parameters derived from simplified thermodynamic and combustion sub-models. The performance of the model is discussed for both a heavy-duty and a light-duty diesel engines. The model behavior is evaluated under input uncertainty so as to provide realistic performance bounds.

A structured approach to uncertainty analysis of predictive models of engine-out NOx emissions

Predictive models of engine-out NOx emissions continue to be a topic of active research in the diesel powertrain community. Renewed interest in the use of in-cylinder pressure sensor has presented an opportunity for improving these models through the availability of direct information about the in-cylinder combustion process. Despite several research efforts in this domain seen in open literature, there is a significant paucity of work that reports on the uncertainty analysis of such models. These models are typically designed for real-time implementation, and the model prediction is often used for control and/or diagnostic functions. It is therefore critical to establish the expected error bounds or an error probability distribution and the model prediction for consideration during the design of relevant control and/or diagnostic algorithms.