Abstract : 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.

A bottom-up approach that enables readers to master and apply the latest techniques in state estimation This book offers the best mathematical approaches to estimating the state of a general system. The author presents state estimation theory clearly and rigorously, providing the right amount of advanced material, recent research results, and references to enable the reader to apply state estimation techniques confidently across a variety of fields in science and engineering. While there are other textbooks that treat state estimation, this one offers special features and a unique perspective and pedagogical approach that speed learning: * Straightforward, bottom-up approach begins with basic concepts and then builds step by step to more advanced topics for a clear understanding of state estimation * Simple examples and problems that require only paper and pen to solve lead to an intuitive understanding of how theory works in practice * MATLAB(r)-based source code that corresponds to examples in the book, available on the author's Web site, enables readers to recreate results and experiment with other simulation setups and parameters Armed with a solid foundation in the basics, readers are presented with a careful treatment of advanced topics, including unscented filtering, high order nonlinear filtering, particle filtering, constrained state estimation, reduced order filtering, robust Kalman filtering, and mixed Kalman/H? filtering. Problems at the end of each chapter include both written exercises and computer exercises. Written exercises focus on improving the reader's understanding of theory and key concepts, whereas computer exercises help readers apply theory to problems similar to ones they are likely to encounter in industry. With its expert blend of theory and practice, coupled with its presentation of recent research results, Optimal State Estimation is strongly recommended for undergraduate and graduate-level courses in optimal control and state estimation theory. It also serves as a reference for engineers and science professionals across a wide array of industries.

In recent years, more and more research attention has been paid to the NOx emissions caused by marine diesel engines. Selective catalytic reduction (SCR) system has been proven to be an effective technology for the removal of NOx emitted from marine diesel engines. In order to comply with stringent International Maritime Organization (IMO) Tier III NOx emission regulations, a number of engine manufacturers have developed their own SCR systems with an option of installing SCR reactors before or after the turbines of engine turbochargers. This thesis focuses on modelling of evaporation and decomposition of urea-water-solution (UWS) droplets, design and optimisation of static mixers, modelling of an SCR reactor and developing model-based urea dosing control strategy.The amount of ammonia converted from UWS has a significant effect on the NOx removal efficiency of SCR systems. Due to a limited installation space for SCR systems on board, choosing the location of urea injection nozzle appropriately has become a critical issue for SCR system design. An evaporation and decomposition model of UWS droplets has been developed in this research in order to determine the total depletion time of a UWS droplet, which is helpful to calculate the proper length between the urea nozzle and reactor of an SCR system.In order to achieve a high NOx removal rate and reduce the quantity of NH3 slip, static mixers are commonly used before SCR reactors to improve the mixing between ammonia and exhaust gases. 4 novel static mixers have been designed and the performance of the mixers is compared in the study. An experiment has been conducted to validate the mixing performance and pressure loss of the static mixers developed. It shows that there is a satisfied agreement between the simulation and experiment results.A mathematical model of SCR reactors has been established. The unknown parameters of the model are identified by minimising the error between the model predicted and measured values of both the temperature and the species concentration after the SCR reactor. The SCR reactor model is further used in a simulation for the purpose of developing model-based urea dosing control strategies.A state observer is used to determine the actual states in the reactor which supplies the mandatory information for developing model-based urea dosing control strategies. The NH3 cross-sensitivity of NOx sensors can be described by a linear equation. The simulation results of the observer show that the NH3 cross-sensitivity of NOx sensors can be neglected when estimating the actual states of the reactor if NH3 is of a low concentration in the exhaust.

A rigorous introduction to the theory and applications of state estimation and association, an important area in aerospace, electronics, and defense industries. Applied state estimation and association is an important area for practicing engineers in aerospace, electronics, and defense industries, used in such tasks as signal processing, tracking, and navigation. This book offers a rigorous introduction to both theory and application of state estimation and association. It takes a unified approach to problem formulation and solution development that helps students and junior engineers build a sound theoretical foundation for their work and develop skills and tools for practical applications. Chapters 1 through 6 focus on solving the problem of estimation with a single sensor observing a single object, and cover such topics as parameter estimation, state estimation for linear and nonlinear systems, and multiple model estimation algorithms. Chapters 7 through 10 expand the discussion to consider multiple sensors and multiple objects. The book can be used in a first-year graduate course in control or system engineering or as a reference for professionals. Each chapter ends with problems that will help readers to develop derivation skills that can be applied to new problems and to build computer models that offer a useful set of tools for problem solving. Readers must be familiar with state-variable representation of systems and basic probability theory including random and stochastic processes.

The selective catalytic reduction (SCR) is a technology used for reducing NO x emissions in the heavy-duty diesel (HDD) engine exhaust. In this study, the spatially resolved capillary inlet infrared spectroscopy (Spaci-IR) technique was used to study the gas concentration and NH3 storage distributions in a SCR catalyst, and to provide data for developing a SCR model to analyze the axial gaseous concentration and axial distributions of NH3 storage. A two-site SCR model is described for simulating the reaction mechanisms. The model equations and a calculation method was developed using the Spaci-IR measurements to determine the NH3 storage capacity and the relationships between certain kinetic parameters of the model. Moreover, a calibration approach was then applied for tuning the kinetic parameters using the spatial gaseous measurements and calculated NH3 storage as a function of axial position instead of inlet and outlet gaseous concentrations of NO, NO2, and NH3. The equations and the approach for determining the NH3 storage capacity of the catalyst and a method of dividing the NH3 storage capacity between the two storage sites are presented. It was determined that the kinetic parameters of the adsorption and desorption reactions have to follow certain relationships for the model to simulate the experimental data. Finally, the modeling results served as a basis for developing full model calibrations to SCR lab reactor and engine data and state estimator development as described in the references (Song et al. 2013a, b; Surenahalli et al. 2013).