scholarly journals Research on Influence of Exhaust Characteristics and Control Strategy to DOC-Assisted Active Regeneration of DPF

Processes ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 1403
Author(s):  
Guanlin Liu ◽  
Weiqiang Liu ◽  
Yibin He ◽  
Jinke Gong ◽  
Qiong Li
Keyword(s):  
Control Strategy ◽  
Diesel Oxidation Catalyst ◽  
Oxidation Catalyst ◽  
Particulate Filter ◽  
Maximum Temperature ◽  
Exhaust Temperature ◽  
Thermal Phenomenon ◽  
Dpf Regeneration ◽  
Soot Loading ◽  
Active Regeneration

For the purpose of designing a reasonable control strategy for DOC-assisted DPF regeneration, a mathematical model that describes the thermal phenomenon both in a diesel oxidation catalyst (DOC) and diesel particulate filter (DPF) during regeneration is developed. All boundary conditions of this model are obtained by experiments. The effects of the main exhaust parameters such as exhaust mass flow rate, exhaust temperature, oxygen concentration and emission of reactants are investigated comprehensively. The effects of two main parameters of control strategy, DOC-out temperature and soot loading, are analyzed as well. To quantify the effects of relevant parameters, the fuzzy grey relational analysis method is utilized to evaluate the correlation coefficient of all factors to key indexes of DPF regeneration such as maximum temperature, maximum rate of temperature increase and regeneration duration. The results of this work will greatly reduce the complexity of analysis and enable more rational control strategy design of DOC–DPF regeneration systems.

Experimental study of lubricant-derived ash effects on diesel particulate filter performance

2019 ◽  
pp. 146808741987457 ◽  
Author(s):  
Jun Zhang ◽  
Yanfei Li ◽  
Victor W Wong ◽  
Shijin Shuai ◽  
Jinzhu Qi ◽  
...  
Keyword(s):  
Pressure Drop ◽  
Diesel Particulate Filter ◽  
Particulate Filter ◽  
Maximum Temperature ◽  
Particle Emissions ◽  
Diesel Particulate ◽  
Particulate Filters ◽  
Filter Performance ◽  
Soot Loading ◽  
Active Regeneration

Diesel particulate filters are indispensable for diesel engines to meet the increasingly stringent emission regulations. A large amount of ash would accumulate in the diesel particulate filter over time, which would significantly affect the diesel particulate filter performance. In this work, the lubricant-derived ash effects on diesel particulate filter pressure drop, diesel particulate filter filtration performance, diesel particulate filter temperature field during active regeneration, and diesel particulate filter downstream emissions during active regeneration were studied on an engine test bench. The test results show that the ash accumulated in the diesel particulate filter would decrease the diesel particulate filter pressure drop due to the “membrane effect” when the diesel particulate filter ash loading is lower than about 10 g/L, beyond which the diesel particulate filter pressure drop would be increased due to the reduction of diesel particulate filter effective volume. The ash loaded in the diesel particulate filter could significantly improve the diesel particulate filter filtration efficiency because it would fill the pores of diesel particulate filter wall. The diesel particulate filter peak temperature during active regeneration is consistent with the diesel particulate filter initial actual soot loading density prior to regeneration at various diesel particulate filter ash loading levels, while the diesel particulate filter maximum temperature gradient would increase with the diesel particulate filter ash loading increase, whether the diesel particulate filter is regenerated at the same soot loading level or the same diesel particulate filter pressure drop level. The ash accumulation in the diesel particulate filter shows little effects on diesel particulate filter downstream CO, total hydrocarbons, N2O emissions, and NO2/NO x ratio during active regeneration. However, a small amount of SO2 emissions was observed when the diesel particulate filter ash loading is higher than 10 g/L. The ash accumulated in the diesel particulate filter would increase the diesel particulate filter downstream sub-23 nm particle emissions but decrease larger particle emissions during active regeneration.

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.

Effects of B20 on Emissions and the Performance of a Diesel Particulate Filter in a Light-Duty Diesel Engine

2009 ◽  
Author(s):  
Amy M. Peterson ◽  
Po-I Lee ◽  
Ming-Chia Lai ◽  
Ming-Cheng Wu ◽  
Craig L. DiMaggio ◽  
...  
Keyword(s):  
Diesel Engine ◽  
Diesel Particulate Filter ◽  
Oxidation Catalyst ◽  
Engine Oil ◽  
Particulate Filter ◽  
Oil Viscosity ◽  
Regeneration Rate ◽  
Diesel Particulate ◽  
Light Duty ◽  
Active Regeneration

This paper compares 20% bio-diesel (B20-choice white grease) fuel with baseline ultra low sulfur diesel (ULSD) fuel on the emissions and performance of a diesel oxidation catalyst (DOC) and diesel particulate filter (DPF) coupled to a light-duty 4-cylinder 2.8-liter common-rail DI diesel engine. The present paper focuses on the comparison of the fuel effects on loading and active regeneration of the DPF between B20 and ULSD. B20, in general, produces less soot and has lower regeneration temperature compared to soot loaded with ULSD. NO2 concentrations before the DPF were found to be 6% higher with B20, indicating more availability of NO2 to oxidize the soot. Exhaust speciation of the NO2 availability indicates that the slight increase in NOx from B20 is not the dominant cause for the lower temperature regeneration and faster regeneration rate but the reactivity of the soot that is in the DPF. Formaldehyde concentrations are found to be higher with B20 during regeneration due to increased oxygen concentrations in the exhaust stream. Finally the oil dilution effect due to post injection to actively regenerate the DPF is also investigated using a prototype oil sensor and FTIR instrumentation. Utilizing an active regeneration strategy accentuates the possibility of fuel oil dilution of the engine oil. The onboard viscosity oil sensor used was in good agreement with the viscosity bench test and FTIR analysis and provided oil viscosity measurement over the course of the project. Operation with B20 shows significant fuel dilution and needs to be monitored to prevent engine deterioration.

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.

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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