DEVELOPMENT OF A HIGH-FIDELITY MODEL AND KALMAN FILTER BASED STATE ESTIMATOR FOR SIMULATION AND CONTROL OF NOX REDUCTION PERFORMANCE OF A SCR CATALYST ON A DPF
Date of Award
Open Access Master's Report
Master of Science in Mechanical Engineering (MS)
Administrative Home Department
Department of Mechanical Engineering-Engineering Mechanics
Gordon G Parker
John H Johnson
Committee Member 1
Jeffery D. Naber
Committee Member 2
Sunil S. Mehendale
Reduction of emissions and improving the fuel consumption are two prime research areas in Diesel engine development. The present after-treatment systems being used for emissions control include diesel oxidation catalyst (DOC) for NO, HC and CO oxidation along with catalyzed particulate filters for PM (particulate matter) and selective catalytic reduction (SCR) for controlling NOx emissions. Recently an after-treatment system called SCR catalyst on a DPF capable of simultaneously reducing both NOx and PM emissions has been developed in order to reduce the overall size of the after-treatment system.
The goal of this proposed research is to create a state estimator that is capable of estimating the internal states of temperature distribution, PM distribution, NH3 storage faction as well as pressure drop across the filter and outlet concentration of NO, NO2 and NH3 for different operating conditions. This would help in achieving an optimal urea dosing strategy during NOx reduction as well as an optimum fuel dosing strategy during active regeneration for the SCR catalyst on a DPF. The motivation for this research comes from the desire to quantify the interaction of SCR reactions and PM oxidation in the SCR catalyst on a DPF and to use the mathematical model created in the process to develop a state estimator that can provide optimal control and onboard diagnostics of combined SCR catalyst on a DPF devices.
In the initial phase of the research a high-fidelity SCR-F model is being developed in MATLAB/Simulink which is capable of predicting the filtration efficiency, temperature distribution, PM distribution, pressure drop across the filter and outlet concentrations of NO, NO2 and NH3. This model will be calibrated using experimental data collected on a Cummins 2013 ISB SCRF®. After the validation of the SCR-F model, the high-fidelity SCR-F model developed will be used with an existing 1D SCR model to perform NOx reduction studies on a system consisting of SCRF® + SCR using experimental data. This step will be followed by development of a reduced order SCR-F model using a coarser mesh (e.g. 5x5 vs 10x10) and simplified governing equations which will also be used as the mathematical model for the state estimator. SCR-F state estimator will be developed to accurately predict the internal states of NH3 coverage fraction, temperature distribution, PM distribution and pressure drop across the SCR catalyst on the DPF. The estimator will be validated using experimental data.
Chundru, Venkata Rajesh, "DEVELOPMENT OF A HIGH-FIDELITY MODEL AND KALMAN FILTER BASED STATE ESTIMATOR FOR SIMULATION AND CONTROL OF NOX REDUCTION PERFORMANCE OF A SCR CATALYST ON A DPF", Open Access Master's Report, Michigan Technological University, 2017.
Acoustics, Dynamics, and Controls Commons, Automotive Engineering Commons, Energy Systems Commons