Experimental and Modeling Results Comparing Two Diesel Oxidation Catalyst - Catalyzed Particulate Filter Systems

2008 ◽  
Author(s):  
Rayomand H. Dabhoiwala ◽  
John H. Johnson ◽  
Jeffrey Naber ◽  
Susan T. Bagley
Keyword(s):  
Diesel Oxidation Catalyst ◽  
Oxidation Catalyst ◽  
Particulate Filter ◽  
Diesel Oxidation ◽  
Catalyzed Particulate Filter

scholarly journals Development of a Kalman filter estimator for simulation and control of particulate matter distribution of a diesel catalyzed particulate filter

2018 ◽  
Vol 21 (5) ◽  
pp. 866-884 ◽  
Author(s):  
Boopathi Singalandapuram Mahadevan ◽  
John H Johnson ◽  
Mahdi Shahbakhti
Keyword(s):  
Particulate Matter ◽  
Pressure Drop ◽  
Mass Distribution ◽  
Diesel Oxidation Catalyst ◽  
Oxidation Catalyst ◽  
Particulate Filter ◽  
Filter Model ◽  
Reduced Order ◽  
Diesel Oxidation ◽  
Catalyzed Particulate Filter

The knowledge of the temperature and particulate matter mass distribution is essential for monitoring the performance and durability of a catalyzed particulate filter. A catalyzed particulate filter model was developed, and it showed capability to accurately predict temperature and particulate matter mass distribution and pressure drop across the catalyzed particulate filter. However, the high-fidelity model is computationally demanding. Therefore, a reduced order multi-zone particulate filter model was developed to reduce computational complexity with an acceptable level of accuracy. In order to develop a reduced order model, a parametric study was carried out to determine the number of zones necessary for aftertreatment control applications. The catalyzed particulate filter model was further reduced by carrying out a sensitivity study of the selected model assumptions. The reduced order multi-zone particulate filter model with 5 × 5 zones was selected to develop a catalyzed particulate filter state estimator considering its computational time and accuracy. Next, a Kalman filter–based catalyzed particulate filter estimator was developed to estimate unknown states of the catalyzed particulate filter such as temperature and particulate matter mass distribution and pressure drop (Δ P) using the sensor inputs to the engine electronic control unit and the reduced order multi-zone particulate filter model. A diesel oxidation catalyst estimator was also integrated with the catalyzed particulate filter estimator in order to provide estimates of diesel oxidation catalyst outlet concentrations of NO2 and hydrocarbons and inlet temperature for the catalyzed particulate filter estimator. The combined diesel oxidation catalyst–catalyzed particulate filter estimator was validated for an active regeneration experiment. The validation results for catalyzed particulate filter temperature distribution showed that the root mean square temperature error by using the diesel oxidation catalyst–catalyzed particulate filter estimator is within 3.2 °C compared to the experimental data. Similarly, the Δ P estimator closely simulated the measured total Δ P and the estimated cake pressure drop error is within 0.2 kPa compared to the high-fidelity catalyzed particulate filter model.

Development of a Low Emissions Upgrade Kit for EMD GP20D and GP15D Locomotives

2012 ◽  
Author(s):  
Steven G. Fritz ◽  
John C. Hedrick ◽  
Tom Weidemann
Keyword(s):  
Fuel Injection ◽  
Diesel Oxidation Catalyst ◽  
Oxidation Catalyst ◽  
Particulate Filter ◽  
Injection Timing ◽  
Fuel Injection Timing ◽  
Tier 1 ◽  
Emission Regulations ◽  
Diesel Oxidation ◽  
Tier 3

This paper describes the development of a low emissions upgrade kit for EMD GP20D and GP15D locomotives. These locomotives were originally manufactured in 2001, and met EPA Tier 1 locomotive emission regulations. The 1,491 kW (2,000 HP) EMD GP20D locomotives are powered by Caterpillar 3516B engines, and the 1,119 kW (1,500 HP) EMD GP15D locomotives are powered by Caterpillar 3512B engines. CIT Rail owns a fleet of 50 of these locomotives that are approaching their mid-life before first overhaul. Baseline exhaust emissions testing was followed by a low emissions retrofit development focusing on fuel injection timing, crankcase ventilation filtration, and application of a diesel oxidation catalyst (DOC), and then later a diesel particulate filter (DPF). The result was a EPA Tier 0+ certification of the low emissions upgrade kit, with emission levels below EPA Line-Haul Tier 3 NOx, and Tier 4 HC, CO, and PM levels.

scholarly journals Control-oriented modeling of diesel oxidation catalyst

2021 ◽  
Vol 268 ◽  
pp. 01027
Author(s):  
Ying Gao ◽  
Hongqi Liu
Keyword(s):  
Temperature Response ◽  
Diesel Oxidation Catalyst ◽  
Oxidation Catalyst ◽  
Particulate Filter ◽  
Outlet Temperature ◽  
Model Structure ◽  
Order Model ◽  
Third Order ◽  
Diesel Oxidation ◽  
Catalyst Model

Diesel oxidation catalyst outlet temperature control is crucial for heat management to realize diesel particulate filter active regenerative control. In order to control the temperature of the active regeneration process in the filter, the temperature response process of the semi-physical oxidation catalyst model structure is proposed as a multi-stage inertia plus delay, and the equivalent inlet temperature step of the fuel oxidation reaction of the exhaust pipe. Combined with the test test, the control oriented oxidation catalyst model is established.A control-oriented oxidation catalyst model was constructed. By analysed the oxidation catalyst working process, the main chemical reactions, heat and mass transfer processes occurring inside the carrier were analyzed. Three-dimensional CFD model and one-dimensional chemical reaction kinetics model were established respectively. The radial and axial temperature distribution of the carrier was analyzed by model simulation. Based on the analysis of the system characteristics, the multi-step inertia plus delay semi-physical model structure was proposed. Combined with the test, the control oriented oxidation catalyst model is established. Select the appropriate working conditions to identify and verify the model parameters. The results show that the third order model can well indicate the temperature response characteristics of the oxidation catalyst outlet temperature. Considering the complexity of the system, the first-order and third-order model are selected as the basis of the control system design.

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