Regimes of spray vaporization and combustion in counterflow configurations

This article addresses the problem of spray vaporization and combustion in axisymmetric opposed-jet configurations involving a stream of hot air counterflowing against a stream of nitrogen carrying a spray of fuel droplets. The Reynolds numbers of the jets are assumed to be large, so that mixing of the two streams is restricted to a thin mixing layer that separates the counterflowing streams. The evolution of the droplets in their feed stream from the injection location is seen to depend fundamentally on the value of the droplet Stokes number, St, defined as the ratio of the droplet acceleration time to the mixing layer strain time close to the stagnation point. Two different regimes of spray vaporization and combustion can be identified depending on the value of St. For values of St below a critical value, equal to 1/4 for dilute sprays with small values of the spray liquid mass loading ratio, the droplets decelerate to approach the gas stagnation plane with a vanishing axial velocity. In this case, the droplets located initially near the axis reach the mixing layer, where they can vaporize due to the heat received from the hot air, producing fuel vapor that can burn with the oxygen in a diffusion flame located on the air side of the mixing layer. The character of the spray combustion is different for values of St of order unity, because the droplets cross the stagnation plane and move into the opposing air stream, reaching distances that are much larger than the mixing layer thickness before they turn around. The vaporization of these crossing droplets, and also the combustion of the fuel vapor generated by them, occur in the hot air stream, without significant effects of molecular diffusion, generating a vaporization-assisted nonpremixed flame that stands on the air side outside the mixing layer. Separate formulations will be given below for these two regimes of combustion, with attention restricted to the near-stagnation-point region, where the solution is self-similar and all variables are only dependent on the distance to the stagnation plane. The resulting formulations display a reduced number of controlling parameters that effectively embody dependences of the structure of the spray flame on spray dilution, droplet inertia, and fuel preferential diffusion. Sample solutions are given for the limiting cases of pure vaporization and of infinitely fast chemistry, with the latter limit formulated in terms of chemistry-free coupling functions that allow for general nonunity Lewis numbers of the fuel vapor.

Effect of rare earth dopants on structural and mechanical properties of nanoceria synthesized by combustion method

Structural characteristics of combustion synthesized, calcined and densified pure and doped nanoceria with tri-valent cations of Er, Y, Gd, Sm and Nd were analyzed by X-ray diffraction (XRD) and high resolution transmission electron microscopy (HRTEM). The results showed that the as-synthesized and calcined nanopowders were mesoporous and calculated lattice parameters were close to theoretical ion-packing model. The effect of dopants on elastic modulus, microhardness and fracture toughness of sintered pure and doped ceria were investigated. It was observed that tri-valent cation dopants increased the hardness of the ceria, whereas the fracture toughness and elastic modulus were decreased.

High performance of Cu/CeO2-Nb2O5 catalysts for preferential CO oxidation and total combustion of toluene

Copper-based catalysts supported on niobium-doped ceria have been prepared and tested in the preferential oxidation of CO in excess of H2 (PROX) and in total oxidation of toluene. Supports and catalysts have been characterized by several techniques: N2 adsorption, ICP-OES, XRF, XRD, Raman Spectroscopy, SEM, TEM, H2-TPR and XPS, and their catalytic performance has been measured in PROX, with an ideal gas mixture (CO, O2 and H2) with or without CO2 and H2O, and in total oxidation of toluene. The effects of the copper loading and the amount of niobium in the supports have been evaluated. Remarkably, the addition of niobia to the catalysts may improve the catalytic performance in total oxidation of toluene. It allows us to prepare cheaper catalysts (niobia it is far cheaper than ceria) with improved catalytic performance.

Post-combustion CO2 adsorption on activated carbons with different textural properties

Fixed bed CO2 adsorption tests were carried out in model flue-gas streams onto two commercial activated carbons, namely Filtrasorb 400 and Nuchar RGC30, at 303 K, 323 K and 353 K. Thermodynamic adsorption results highlighted that the presence of a narrower micropore size distribution with a prevailing contribution of very small pore diameters, observed for Filtrasorb 400, is a key factor in determining a higher CO2 capture capacity, mostly at low temperature. These experimental evidences were also corroborated by the higher value of the isosteric heat derived for Filtrasorb 400, testifying stronger interactions with CO2 molecules with respect to Nuchar RGC30. Dynamic adsorption results on the investigated sorbents highlighted the important role played by both a greater contribution of mesopores and the presence of wider micropores for Nuchar RGC30 in establishing faster capture kinetics with respect to Filtrasorb 400, in particular at 303 K. Furthermore, the modeling analysis of 15% CO2 breakthrough curves allowed identifying intraparticle diffusion as the rate-determining step of the process.

Active oxygen by Ce–Pr mixed oxide nanoparticles outperform diesel soot combustion Pt catalysts

A Ce0.5Pr0.5O2 mixed oxide has been prepared with the highest surface area and smallest particle size ever reported (125 m2/g and 7 nm, respectively), also being the most active diesel soot combustion catalyst ever tested under realistic conditions if catalysts forming highly volatile species are ruled out. This Ce–Pr mixed oxide is even more active than a reference platinum-based commercial catalyst. This study provides an example of the efficient participation of oxygen species released by a ceria catalyst in a heterogeneous catalysis reaction where both the catalyst and one of the reactants (soot) are solids. It has been concluded that both the ceria-based catalyst composition (nature and amount of dopant) and the particle size play key roles in the combustion of soot through the active oxygen-based mechanism. The composition determines the production of active oxygen and the particle size the transfer of such active oxygen species from catalyst to soot.

Effect of the CeZrNd mixed oxide synthesis method in the catalytic combustion of soot

Ce0.64Zr0.27Nd0.09Oδ mixed oxides have been prepared by three different methods (nitrates calcination, coprecipitation and microemulsion), characterized by N2 adsorption, XRD, H2-TPR, Raman spectroscopy and XPS, and tested for soot combustion in NOx/O2. The catalyst prepared by microemulsion method is the most active one, which is related to its high surface area (147 m2/g) and low crystallite size (6 nm), and the lowest activity was obtained with the catalyst prepared by coprecipitation (74 m2/g; 9 nm). The catalyst prepared by nitrates precursors calcination is slightly less active to that prepared by microemulsion, but the synthesis procedure is very straightforward and surfactants or other chemicals are not required, being very convenient for scaling up and practical utilization. The high activity of the catalyst prepared by nitrates calcination can be attributed to the better introduction of Nd cations into the parent ceria framework than on catalysts prepared by coprecipitation and microemulsion, which promotes the creation of more oxygen vacancies.

Opportunities for ceria-based mixed oxides versus commercial platinum-based catalysts in the soot combustion reaction. Mechanistic implications

The aim of this paper is to study the activities of ceria–zirconia and copper/ceria–zirconia catalysts, comparing with a commercial platinum/alumina catalyst, for soot combustion reaction under different gas atmospheres and loose contact mode (simulating diesel exhaust conditions), in order to analyse the kinetics and to deduce mechanistic implications. Activity tests were performed under isothermal and TPR conditions. The NO oxidation to NO2 was studied as well. It was checked that mass transfer limitations were not influencing the rate measurements. Global activation energies for the catalysed and non-catalysed soot combustion were calculated and properly discussed. The results reveal that ceria-based catalysts greatly enhance their activities under NOx/O2 between 425 °C and 450 °C, due to the “active oxygen”-assisted soot combustion. Remarkably, copper/ceria–zirconia shows a slightly higher soot combustion rate than the Pt-based catalyst (under NOx/O2, at 450 °C).

Novel Automotive Waste Heat Recovery Techniques

The United States transportation industry is predicted to consume approximately 13 million barrels of liquid fuel per day by 2025. If one percent of the fuel energy were salvaged through waste heat recovery, there would be a reduction of 130 thousand barrels of liquid fuel per day. This dissertation focuses on automotive waste heat recovery techniques with an emphasis on two novel techniques. The first technique investigated was a combination coolant and exhaust-based Rankine cycle system, which utilized a patented piston-in-piston engine technology. The research scope included a simulation of the maximum mass flow rate of steam (700 K and 5.5 MPa) from two heat exchangers, the potential power generation from the secondary piston steam chambers, and the resulting steam quality within the steam chamber. The secondary piston chamber provided supplemental steam power strokes during the engine's compression and exhaust strokes to reduce the pumping work of the engine. A Class-8 diesel engine, operating at 1,500 RPM at full load, had a maximum increase in the brake fuel conversion efficiency of 3.1%. The second technique investigated the implementation of thermoelectric generators on the outer cylinder walls of a liquid-cooled internal combustion engine. The research scope focused on the energy generation, fuel energy distribution, and cylinder wall temperatures. The analysis was conducted over a range of engine speeds and loads in a two cylinder, 19.4 kW, liquid-cooled, spark-ignition engine. The cylinder wall temperatures increased by 17% to 44% which correlated well to the 4.3% to 9.5% decrease in coolant heat transfer. Only 23.3% to 28.2% of the heat transfer to the coolant was transferred through the TEG and TEG surrogate material. The gross indicated work decreased by 0.4% to 1.0%. The exhaust gas energy decreased by 0.8% to 5.9%. Due to coolant contamination, the TEG output was not able to be obtained. TEG output was predicted from cylinder wall temperatures and manufacturer documentation, which was less than 0.1% of the cumulative heat release. Higher TEG conversion efficiencies, combined with greater control of heat transfer paths, would be needed to improve energy output and make this a viable waste heat recovery technique.

MODELING AND EXPERIMENTAL SETUP OF AN HCCI ENGINE

For the past three decades the automotive industry is facing two main conflicting challenges to improve fuel economy and meet emissions standards. This has driven the engineers and researchers around the world to develop engines and powertrain which can meet these two daunting challenges. Focusing on the internal combustion engines there are very few options to enhance their performance beyond the current standards without increasing the price considerably. The Homogeneous Charge Compression Ignition (HCCI) engine technology is one of the combustion techniques which has the potential to partially meet the current critical challenges including CAFE standards and stringent EPA emissions standards. HCCI works on very lean mixtures compared to current SI engines, resulting in very low combustion temperatures and ultra-low NOx emissions. These engines when controlled accurately result in ultra-low soot formation. On the other hand HCCI engines face a problem of high unburnt hydrocarbon and carbon monoxide emissions. This technology also faces acute combustion controls problem, which if not dealt properly with yields highly unfavorable operating conditions and exhaust emissions. This thesis contains two main parts. One part deals in developing an HCCI experimental setup and the other focusses on developing a grey box modelling technique to control HCCI exhaust gas emissions. The experimental part gives the complete details on modification made on the stock engine to run in HCCI mode. This part also comprises details and specifications of all the sensors, actuators and other auxiliary parts attached to the conventional SI engine in order to run and monitor the engine in SI mode and future SI-HCCI mode switching studies. In the latter part around 600 data points from two different HCCI setups for two different engines are studied. A grey-box model for emission prediction is developed. The grey box model is trained with the use of 75% data and the remaining data is used for validation purpose. An average of 70% increase in accuracy for predicting engine performance is found while using the grey-box over an empirical (black box) model during this study. The grey-box model provides a solution for the difficulty faced for real time control of an HCCI engine. The grey-box model in this thesis is the first study in literature to develop a control oriented model for predicting HCCI engine emissions for control.

MODELING OF TRANSFER PATH FOR DETERMINATION OF COMBUSTION AND NOISE METRICS ON DIESEL ENGINES

Determination of combustion metrics for a diesel engine has the potential of providing feedback for closed-loop combustion phasing control to meet current and upcoming emission and fuel consumption regulations. This thesis focused on the estimation of combustion metrics including start of combustion (SOC), crank angle location of 50% cumulative heat release (CA50), peak pressure crank angle location (PPCL), and peak pressure amplitude (PPA), peak apparent heat release rate crank angle location (PACL), mean absolute pressure error (MAPE), and peak apparent heat release rate amplitude (PAA). In-cylinder pressure has been used in the laboratory as the primary mechanism for characterization of combustion rates and more recently in-cylinder pressure has been used in series production vehicles for feedback control. However, the intrusive measurement with the in-cylinder pressure sensor is expensive and requires special mounting process and engine structure modification. As an alternative method, this work investigated block mounted accelerometers to estimate combustion metrics in a 9L I6 diesel engine. So the transfer path between the accelerometer signal and the in-cylinder pressure signal needs to be modeled. Depending on the transfer path, the in-cylinder pressure signal and the combustion metrics can be accurately estimated - recovered from accelerometer signals. The method and applicability for determining the transfer path is critical in utilizing an accelerometer(s) for feedback. Single-input single-output (SISO) frequency response function (FRF) is the most common transfer path model; however, it is shown here to have low robustness for varying engine operating conditions. This thesis examines mechanisms to improve the robustness of FRF for combustion metrics estimation. First, an adaptation process based on the particle swarm optimization algorithm was developed and added to the single-input single-output model. Second, a multiple-input single-output (MISO) FRF model coupled with principal component analysis and an offset compensation process was investigated and applied. Improvement of the FRF robustness was achieved based on these two approaches. Furthermore a neural network as a nonlinear model of the transfer path between the accelerometer signal and the apparent heat release rate was also investigated. Transfer path between the acoustical emissions and the in-cylinder pressure signal was also investigated in this dissertation on a high pressure common rail (HPCR) 1.9L TDI diesel engine. The acoustical emissions are an important factor in the powertrain development process. In this part of the research a transfer path was developed between the two and then used to predict the engine noise level with the measured in-cylinder pressure as the input. Three methods for transfer path modeling were applied and the method based on the cepstral smoothing technique led to the most accurate results with averaged estimation errors of 2 dBA and a root mean square error of 1.5dBA. Finally, a linear model for engine noise level estimation was proposed with the in-cylinder pressure signal and the engine speed as components.

AN INVESTIGATION OF VARIABLE VALVE TIMING EFFECTS ON HCCI ENGINE PERFORMANCE

The Homogeneous Charge Compression Ignition (HCCI) engine is a promising combustion concept for reducing NOx and particulate matter (PM) emissions and providing a high thermal efficiency in internal combustion engines. This concept though has limitations in the areas of combustion control and achieving stable combustion at high loads. For HCCI to be a viable option for on-road vehicles, further understanding of its combustion phenomenon and its control are essential. Thus, this thesis has a focus on both the experimental setup of an HCCI engine at Michigan Technological University (MTU) and also developing a physical numerical simulation model called the Sequential Model for Residual Affected HCCI (SMRH) to investigate performance of HCCI engines. The primary focus is on understanding the effects of intake and exhaust valve timings on HCCI combustion. For the experimental studies, this thesis provided the contributions for development of HCCI setup at MTU. In particular, this thesis made contributions in the areas of measurement of valve profiles, measurement of piston to valve contact clearance for procuring new pistons for further studies of high geometric compression ratio HCCI engines. It also consists of developing and testing a supercharging station and the setup of an electrical air heater to extend the HCCI operating region. The HCCI engine setup is based on a GM 2.0 L LHU Gen 1 engine which is a direct injected engine with variable valve timing (VVT) capabilities. For the simulation studies, a computationally efficient modeling platform has been developed and validated against experimental data from a single cylinder HCCI engine. In-cylinder pressure trace, combustion phasing (CA10, CA50, BD) and performance metrics IMEP, thermal efficiency, and CO emission are found to be in good agreement with experimental data for different operating conditions. Effects of phasing intake and exhaust valves are analyzed using SMRH. In addition, a novel index called Fuel Efficiency and Emissions (FEE) index is defined and is used to determine the optimal valve timings for engine operation through the use of FEE contour maps.

Development and Validation of a Model-Based Combustion Controller for Water Injection Management

This manuscript reports the overall development of a Ph.D. research project during the “Mechanics and advanced engineering sciences” course at the Department of Industrial Engineering of the University of Bologna. The project is focused on the development of a combustion control system for an innovative Spark Ignited engine layout. In details, the controller is oriented to manage a prototypal engine equipped with a Port Water Injection system. The water injection technology allows an increment of combustion efficiency due to the knock mitigation effect that permits to keep the combustion phasing closer to the optimal position with respect to the traditional layout. At the beginning of the project, the effects and the possible benefits achievable by water injection have been investigated by a focused experimental campaign. Then the data obtained by combustion analysis have been processed to design a control-oriented combustion model. The model identifies the correlation between Spark Advance, combustion phasing and injected water mass, and two different strategies are presented, both based on an analytic and semi-empirical approach and therefore compatible with a real-time application. The model has been implemented in a combustion controller that manages water injection to reach the best achievable combustion efficiency while keeping knock levels under a pre-established threshold. Three different versions of the algorithm are described in detail. This controller has been designed and pre-calibrated in a software-in-the-loop environment and later an experimental validation has been performed with a rapid control prototyping approach to highlight the performance of the system on real set-up. To further make the strategy implementable on an onboard application, an estimation algorithm of combustion phasing, necessary for the controller, has been developed during the last phase of the PhD Course, based on accelerometric signals.

Numerical assessment of the water injection application to GDI engines

A possible future scenario for the water injection (WI) application has been explored as an advanced strategy for modern GDI engines. The aim is to verify whether the PWI (Port Water Injection) and DWI (Direct Water Injection) architectures can replace current fuel enrichment strategies to limit turbine inlet temperatures (TiT) and knock engine attitude. In this way, it might be possible to extend the stoichiometric mixture condition over the entire engine map, meeting possible future restrictions in the use of AES (Auxiliary Emission Strategies) and future emission limitations. The research was first addressed through a comprehensive assessment of the state-of-the-art of the technology and the main effects of the chemical-physical water properties. Then, detailed chemical kinetics simulations were performed in order to compute the effects of WI on combustion development and auto-ignition. The latter represents an important methodology step for accurate numerical combustion simulations. The water injection was then analysed in detail for a PWI system, through an experimental campaign for macroscopic and microscopic injector characterization inside a test chamber. The collected data were used to perform a numerical validation of the spray models, obtaining an excellent matching in terms of particle size and droplet velocity distributions. Finally, a wide range of three-dimensional CFD simulations of a virtual high-bmep engine were realized and compared, exploring also different engine designs and water/fuel injection strategies under non-reacting and reacting flow conditions. According to the latter, it was found that thanks to the introduction of water, for both PWI and DWI systems, it could be possible to obtain an increase of the target performance and an optimization of the bsfc (Break Specific Fuel Consumption), lowering the engine knock risk at the same time, while the TiT target has been achieved hardly only for one DWI configuration.

Investigation of innovative combustion systems for reduced fuel consumption and increased specific power production

This work resumes a wide variety of research activities carried out with the main objective of increasing the efficiency and reducing the fuel consumption of Gasoline Direct Injection engines, especially under high loads. For this purpose, two main innovative technologies have been studied, Water Injection and Low-Pressure Exhaust Gas Recirculation, which help to reduce the temperature of the gases inside the combustion chamber and thus mitigate knock, being this one of the main limiting factors for the efficiency of modern downsized engines that operate at high specific power. A prototypal Port Water Injection system was developed and extensive experimental work has been carried out, initially to identify the benefits and limitations of this technology. This led to the subsequent development and testing of a combustion controller, which has been implemented on a Rapid Control Prototyping environment, capable of managing water injection to achieve knock mitigation and a more efficient combustion phase. Regarding Low-Pressure Exhaust Gas Recirculation, a commercial engine that was already equipped with this technology was used to carry out experimental work in a similar fashion to that of water injection. Another prototypal water injection system has been mounted to this second engine, to be able to test both technologies, at first separately to compare them on equal conditions, and secondly together in the search of a possible synergy. Additionally, based on experimental data from several engines that have been tested during this study, including both GDI and GCI engines, a real-time model (or virtual sensor) for the estimation of the maximum in-cylinder pressure has been developed and validated. This parameter is of vital importance to determine the speed at which damage occurs on the engine components, and therefore to extract the maximum performance without inducing permanent damages.

Development of advanced methods for the simulation of the reacting mixture formation in internal combustion engines with the use of machine learning algorithms

Besides increasing the share of electric and hybrid vehicles, in order to comply with more stringent environmental protection limitations, in the mid-term the auto industry must improve the efficiency of the internal combustion engine and the well to wheel efficiency of the employed fuel. To achieve this target, a deeper knowledge of the phenomena that influence the mixture formation and the chemical reactions involving new synthetic fuel components is mandatory, but complex and time intensive to perform purely by experimentation. Therefore, numerical simulations play an important role in this development process, but their use can be effective only if they can be considered accurate enough to capture these variations. The most relevant models necessary for the simulation of the reacting mixture formation and successive chemical reactions have been investigated in the present work, with a critical approach, in order to provide instruments to define the most suitable approaches also in the industrial context, which is limited by time constraints and budget evaluations. To overcome these limitations, new methodologies have been developed to conjugate detailed and simplified modelling techniques for the phenomena involving chemical reactions and mixture formation in non-traditional conditions (e.g. water injection, biofuels etc.). Thanks to the large use of machine learning and deep learning algorithms, several applications have been revised or implemented, with the target of reducing the computing time of some traditional tasks by orders of magnitude. Finally, a complete workflow leveraging these new models has been defined and used for evaluating the effects of different surrogate formulations of the same experimental fuel on a proof-of-concept GDI engine model.