This diploma thesis deals with the issue of nitrogen oxides emissions in exhaust gases and possibilities of their reduction. The task of the thesis was analysis of systems for NOX reduction by contemporary diesel engines, design and construction of NOX reduction device for given diesel engine, then verify functionality of this system compiled from commercially available components. In the last part of thesis available measurements will be made with an analysis of achieved results.

Indiana University-Purdue University Indianapolis (IUPUI) / Stringent regulatory requirements and modern diesel engine technologies have engaged automotive manufacturers and researchers in accurately predicting and controlling diesel engine-out emissions. As a result, engine control systems have become more complex and opaquer, increasing the development time and costs. To address this challenge, Model-based control methods are an effective way to deal with the criticality of the system study and controls. And physics-based combustion engine modeling is a key to achieve it. This thesis focuses on development and validation of a physics-based model for both engine and emissions using model-based design tools from MATLAB & Simulink. Engine model equipped with exhaust gas circulation and variable geometry turbine is adopted from the previously done work which was then integrated with the combustion and emission model that predicts the heat release rates and NOx emission from engine. Combustion model is designed based on the mass fraction burnt from CA10 to CA90 and then NOx predicted using the extended Zeldovich mechanism. The engine models are tuned for both steady state and dynamics test points to account for engine operating range from the performance data. Various engine and combustion parameters are estimated using parameter estimation toolbox from MATLAB and Simulink by applying the least squared solver to minimize the error between measured and estimated variables. This model is validated against the virtual engine model developed in GT-power for Cummins 6.7L turbo diesel engine. To account for the harmonization of the testing cycles to save engine development time globally, a world harmonized stationary cycle (WHSC) is used for the validation. Sub-systems are validated individually as well as in a loop with a complete model for WHSC. Engine model validation showed promising accuracy of more than 88.4 percent on average for the desired parameters required for the NOx prediction. NOx estimation is accurate for the cycle except the warm-up and cool-down phase. However, NOx prediction during these phases is limited due to actual NOx measured data for tuning the model for real-time NOx estimation. Results are summarized at the end to compare the trend of NOx estimation from the developed combustion and emission model to show the accuracy of in-cylinder parameters and required for the NOx estimation.

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Yes / Prediction of engine-out emissions with high fidelity from in-cylinder combustion simulations is still a significant challenge early in the engine development process. This paper contributes to this fast evolving body of knowledge by focusing on the evaluation of NOx emissions predictions capability of a Probability Density Function (PDF) based Stochastic Reactor Engine Models (SRM), for a Diesel engine. The research implements a systematic approach to the study of the SRM engine model performance, based on a detailed space-filling design of experiments based sensitivity analysis of both external and internal parameters, evaluating their effects on the accuracy in matching physical measurements of in-cylinder conditions, and NOx emissions output. The approach proposed in this paper introduces an automatic SRM model calibration methodology across the engine operating envelope, based on a multi-objective optimization approach. This aims to exploit opportunities for internal SRM parameters tuning to achieve good overall modelling performance as a trade-off between physical in-cylinder measurements accuracy and the output NOx emissions predictions error. The results from the case study provide a valuable insight into the effectiveness of the SRM model, showing good capability for NOx emissions prediction and trends, while pointing out the critical sensitivity to the external input parameters and modelling conditions. / 41043/R00836 Jaguar Land Rover funded research “MULTI-PHYSICS ENGINE SIMULATION FRAMEWORK: RESEARCH INTO ADVANCED CAE CAPABILITY FOR MULTI-PHYSICS SIMULATION FRAMEWORK TO GENERATE HIGH FIDELITY PREDICTION OF ENGINE-OUT EMISSIONS”, 2016 – 2019. / Research Development Fund Publication Prize Award winner, March 2019.

Biomass fast pyrolysis liquid (bio-oil) is a cellulose based alternative fuel with the potential to displace fossil fuels in stationary heat and power applications. To better understand the combustion behavior and emissions of bio-oil, a 10 kW spray burner was designed and constructed. The effect of swirl, atomization quality, ignition source (pilot) energy, air/fuel preheat and equivalence ratio on the stability and emissions of bio-oil spray flames was investigated. A blend of 80% pyrolysis liquid and 20% ethanol by volume was used during the tests and the results were compared to burner operation with diesel. It is important to have good atomization, thorough mixing and high swirl in order to stabilize ignition, promote the burnout of bio-oil and decrease CO, hydrocarbon and particulate matter emissions. The total amount of primary air and atomizing air that can be used to improve turbulence, mixing, droplet burnout and overall combustion quality is limited by the distillable fraction and narrow lean blow-out limit associated with pyrolysis liquid. Air and fuel preheat are important for reducing hydrocarbon and CO emissions, although subsequent fuel boiling should be avoided in order to maintain flame stability. The NOx produced in bio-oil flames is dominated by the conversion of fuel bound nitrogen. The particulate matter collected during bio-oil combustion is composed of both carbonaceous cenosphere residues and ash. Under good burning conditions, the majority consists of ash. Pilot flame energy and air/fuel preheat have a weak effect on the total particulate matter in the exhaust. Generally, these results suggest that available burner parameters can be adjusted in order to achieve low hydrocarbon, CO and carbonaceous particulate matter emissions when using pyrolysis liquid. Total particulates can be further mitigated by reducing the inherent ash content in bio-oil. Comparative burner tests with diesel reveal much lower emissions for this fuel at most of the operating points considered. This is due to the fully distillable nature, better atomization and improved spray ignition characteristics associated with diesel. Because of its superior volatility, diesel can also operate over a much wider range of primary air and atomizing air flow rates compared to bio-oil.

Biomass fast pyrolysis liquid (bio-oil) is a cellulose based alternative fuel with the potential to displace fossil fuels in stationary heat and power applications. To better understand the combustion behavior and emissions of bio-oil, a 10 kW spray burner was designed and constructed. The effect of swirl, atomization quality, ignition source (pilot) energy, air/fuel preheat and equivalence ratio on the stability and emissions of bio-oil spray flames was investigated. A blend of 80% pyrolysis liquid and 20% ethanol by volume was used during the tests and the results were compared to burner operation with diesel. It is important to have good atomization, thorough mixing and high swirl in order to stabilize ignition, promote the burnout of bio-oil and decrease CO, hydrocarbon and particulate matter emissions. The total amount of primary air and atomizing air that can be used to improve turbulence, mixing, droplet burnout and overall combustion quality is limited by the distillable fraction and narrow lean blow-out limit associated with pyrolysis liquid. Air and fuel preheat are important for reducing hydrocarbon and CO emissions, although subsequent fuel boiling should be avoided in order to maintain flame stability. The NOx produced in bio-oil flames is dominated by the conversion of fuel bound nitrogen. The particulate matter collected during bio-oil combustion is composed of both carbonaceous cenosphere residues and ash. Under good burning conditions, the majority consists of ash. Pilot flame energy and air/fuel preheat have a weak effect on the total particulate matter in the exhaust. Generally, these results suggest that available burner parameters can be adjusted in order to achieve low hydrocarbon, CO and carbonaceous particulate matter emissions when using pyrolysis liquid. Total particulates can be further mitigated by reducing the inherent ash content in bio-oil. Comparative burner tests with diesel reveal much lower emissions for this fuel at most of the operating points considered. This is due to the fully distillable nature, better atomization and improved spray ignition characteristics associated with diesel. Because of its superior volatility, diesel can also operate over a much wider range of primary air and atomizing air flow rates compared to bio-oil.

A major opportunity for using satellite observations of tropospheric chemical concentrations is to improve our scientific understanding of atmospheric processes by integrated analysis of satellite, aircraft, and ground-based observations with global and regional scale models. One endpoint of such efforts is to reduce modeling biases and uncertainties. The idea of coupling these observations with a regional scale air quality model was the starting point of this research. The overall objective of this research was to improve the NOₓ emission inventories by integrating observations from different platforms and regional air quality modeling. Specific objectives were: 1) Comparison of satellite NO₂ retrievals with simulated NO₂ by the regional air quality model. Comparison of simulated tropospheric gas concentrations simulated by the regional air quality model, with aircraft and ground-based observations; 3) Assessment of the uncertainties in comparing satellite NO₂ retrievals with NOₓ emissions estimates and model simulations; 4) Identification of biases in emission inventories by data assimilation of satellite NO₂ retrievals, and ground-based NO, NO₂ and O₃ observations with an iterative inverse method using the regional air quality model coupled with sensitivity calculations; 5) Improvement of our understanding of NOₓ emissions, and the interaction between regional and global air pollution by an integrated analysis of satellite NO₂ retrievals with the regional air quality model. Along with these objectives, a lightning NOₓ emission inventory was prepared for two months of summer 2004 to account for a significant upper level NOₓ source. Spatially-resolved weekly NO₂ variations from satellite retrievals were compared with estimated NOₓ emissions for different region types. Data assimilation of satellite NO₂ retrievals, and ground-based NO, NO₂ and O₃ observations were performed to evaluate the NOₓ emission inventory. This research contributes to a better understanding of the use of satellite NO₂ retrievals in air quality modeling, and improvements in the NOₓ emission inventories by correcting some of the inconsistencies that were found in the inventories. Therefore, it may provide groups that develop emissions estimates guidance on areas for improvement. In addition, this research indicates the weaknesses and the strengths of the satellite NO₂ retrievals and offers suggestions to improve the quality of the retrievals for further use in the tropospheric air pollution research.

Homogeneously charged spark ignition (SI) engines are unable to stabilise the combustion in ultra lean mixtures, therefore they operate with a near stoichiometric air-fuel ratio (AFR) at all load points. This produces high engine out NOx and CO emissions with a compromise on fuel consumption. Moreover, stoichiometric operation is needed for effective operation of a three way catalyst, which is not adequate to meet future fuel consumption targets. (For complete abstract open document)

O presente trabalho trata da modelagem de combustão em um queimador industrial de gás natural utilizando cadeias de reatores químicos idealizados. A partir de simulações de CFD e dados experimentais do ensaio denominado BERL 300 kW, sucessivas cadeias de reatores são propostas, baseando-se em premissas sobre as condições de temperatura e fluxo de massa entre as diversas regiões do escoamento reativo. O objetivo é obter uma cadeia de reatores que reproduza as emissões de NOx do ensaio. O erro relativo das emissões é de 98,23% na primeira cadeia, de 82,30% na segunda cadeia e de 1,54% na terceira cadeia. A partir da terceira cadeia de reatores proposta, considerada representativa do ensaio, realiza-se uma análise de sensibilidade e um estudo paramétrico, para avaliar a sensibilidade do modelo aos ajustes de segmentação de correntes e a capacidade de reproduzir os dados experimentais de emissão em condições de pré-aquecimento do ar de combustão e em operação fora do ponto de projeto. O modelo produz resultados satisfatórios para os casos de pré-aquecimento do ar até 110°C e para potências térmicas até 33% superiores ao ponto de projeto, não oferecendo bons resultados para as demais condições de operação. / This work shows the development and application of chemical reactor networks (CRN) to the modeling of a natural gas burner. The CRN development is based on experimental and CFD simulation results of the BERL 300 kW test. The CRN element arrangement, reactor volumes and flow splits are adjusted based on the best agreement with characteristic temperatures of the reactive flow, aiming to reproduce the experimental NOx emissions data. The relative error in the emissions predictions are 98,23% for the first CRN proposed, 82,30% for the second CRN and 1,54% for the third one. A sensitivity analysis and a parametric study of the third CRN are carried out to evaluate its sensitivity to the flow splits adjustments and its ability to predict emission with air preheat and turndown operation. The NOx emissions predicted by CRN are in good agreement until 110ºC preheating and for a turndown ratio of 1,33.