Search Results

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.

In this study, a DOC catalyst was experimentally studied in an engine test cell with a2010 Cummins 6.7L ISB diesel and a production aftertreatment system. The test matrix consisted of steady state, active regeneration with in-cylinder fuel dosing and transient conditions. Conversion efficiencies of total hydrocarbon (THC), CO, and NO were quantified under each condition. A previously developed high-fidelity DOC model capable of predicting both steady state and transient active regeneration gaseous emissions was calibrated to the experimental data. The model consists of a single 1D channel where mass and energy balance equations were solved for both surface and bulk gas regions. The steady-state data were used to identify the activation energies and pre-exponential factors for CO, NO and HC oxidation, while the steady-state active regeneration data were used to identify the inhibition factors. The transient data were used to simulate the thermal response of the DOC.

This paper focuses on the development of an Extended Kalman Filter for estimating internal species concentration and storage states of an SCR using NOX and NH₃ sensors. The motivation for this work was twofold. First, knowledge of internal states may be useful for onboard diagnostic strategy development. In particular, significant errors between the outlet NOX or NH₃ sensors, reconstructed from estimated states, and the measured NOX or NH₃ concentrations may aid OBD strategies that attempt to identify particular system failure modes. Second, the EKF described estimates not only stored ammonia but also NO, NO₂ and NH₃ gas concentrations within and exiting the SCR. Exploiting knowledge of the individual species concentrations, instead of lumping them together as NOX, can yield improved closed loop urea controller performance in terms of reduced urea consumption and better NOX conversion.

A numerical model to simulate the filtration and oxidation of PM as well as the oxidation of NO, CO and HC in a CPF was developed in reference [1]. The model consists of parameters related to filtration and oxidation of PM and oxidation of NO, CO and HC. One of the goals of this paper is to use the model to determine the PM and gaseous species kinetics for ULSD, B10 and B20 fuels using data from passive oxidation and active regeneration engine experimental studies. A calibration procedure to identify the PM cake and wall filtration parameters and kinetic parameters for the PM oxidation and NO, CO and HC oxidation was developed. The procedure was then used with the passive oxidation [2] and active regeneration [3] engine data. The tests were conducted on a 2007 Cummins ISL engine with a DOC and CPF aftertreatment system. The simulation results show good agreement with the experimental CPF pressure drop, PM mass retained measurements and the outlet NO, NO2, CO and HC concentrations.

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.

Tailpipe particle number (PN) emission limits for heavy-duty diesel engines have been introduced as part of the off-highway Stage V standards. To meet the required limits a diesel particulate filter (DPF) with high filtration efficiency is required. The DPF relies on formation of a soot cake layer on the channel walls to achieve this high filtration efficiency. Off highway Stage V certification cycles are significantly higher in temperature than their on-highway counterparts, leading to difficulty in creating and maintaining a soot cake in the DPF. Hence for these applications meeting particle number requirements is challenging. To meet the high filtration efficiency requirements the DPF will have to reduce mean pore size, pore standard deviation, and increase wall thickness, in turn increasing backpressure, which results in a fuel consumption penalty. Another option is to evaluate the impact of temperature stable ash accumulation on DPF filtration efficiency.