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Numerical models of aftertreatment devices are increasingly becoming indispensable tools in the development of aftertreatment systems that enable modern diesel engines to comply with exhaust emissions regulations while minimizing the cost and development time involved. Such a numerical model was developed at Michigan Technological University (MTU) [1] and demonstrated to be able to simulate the experimental data [2] in predicting the characteristic pressure drop and PM mass retained during passive oxidation [3] and active regeneration [4] of a catalyzed diesel particulate filter (CPF) on a Cummins ISL engine. One of the critical aspects of a calibrated numerical model is its usability - in other words, how useful is the model in predicting the pressure drop and the PM mass retained in another particulate filter on a different engine without the need for extensive recalibration.

A computer simulation program was developed to simulate the thermal responses of an on-highway, heavy duty diesel powered truck in transient operation for evaluation of cooling system performance. Mathematical models of the engine, heat exchangers, lubricating oil system, thermal control sensors (thermostat and shutterstat), auxiliary components, and the cab were formulated and calibrated to laboratory experimental data. The component models were assembled into the vehicle engine cooling system model and used to predict air-to-boil temperatures. The model has the capability to predict real time coolant, oil and cab temperatures using vehicle simulation input data over various routes.

Diesel Oxidation Catalysts (DOC) are used on heavy duty diesel engine applications and experience large internal temperature variations from 150 to 600°C. The DOC oxidizes the CO and HC in the exhaust to CO2 and H2O and oxidizes NO to NO2. The oxidation reactions are functions of its internal temperatures. Hence, accurate estimation of internal temperatures is important both for onboard diagnostic and aftertreatment closed loop control strategies. This paper focuses on the development of a reduced order model and an Extended Kalman Filter (EKF) state estimator for a DOC. The reduced order model simulation results are compared to experimental data. This is important since the reduced order model is used in the EKF estimator to predict the CO, NO, NO2 and HC concentrations in the DOC and at the outlet. The estimator was exercised using transient drive cycle engine data. The closed loop EKF improves the temperature estimate inside the DOC compared to the open loop estimator.

The catalyzed particulate filter (CPF), used in conjunction with a diesel oxidation catalyst (DOC) is an important aftertreatment device used to meet Environmental Protection Agency (EPA) heavy-duty diesel emission standards for particulate matter (PM). Numerical modeling of these exhaust after-treatment devices decreases the time and cost of development involved. Modeling CPF active regeneration gives insight into the PM oxidation kinetics, which helps in reducing the regeneration fuel penalty. As seen from experimental data, active regeneration of the CPF results in a significant temperature increase into the CPF (up to 8°C/sec) which affects the oxidation rate of particulate matter (PM). PM oxidation during active regeneration was determined to be a function of filter PM loading, inlet temperature and inlet hydrocarbon concentration.