Ethanol, n-propanol, isopropanol, n-butanol, isobutanol, and sec-butanol are six potential carbon-neutral fuels of the future. One application of these carbon-neutral fuels is in high-dilution spark ignition. To understand the potential of these fuels in high-dilution spark ignition, this work experimentally determines the spark ignition lean flammability limit of each fuel with no external, cooled exhaust gas recirculation (EGR), and with 20% external, EGR. The spark ignition lean flammability limit in this work is defined as the excess-air ratio that results in a coefficient of variance of gross indicated mean effective pressure greater than 5%. This is done on an engine with a compression ratio of 12.5, using an intake pressure of 1 bar and an intake temperature of 320 K. It was found that ethanol had the leanest lean limit, due to its high flame speed, followed by n-propanol, isopropanol, and sec-butanol, which all had similar lean limits. n-Butanol and isobutanol had the richest lean limits due their high knock propensity and low flame speed, respectively. The lean limit of each fuel decreased with external, cooled EGR addition, with ethanol as the least sensitive and isopropanol as the most sensitive to EGR addition. Overall, using a high dilution strategy increased the cycle efficiency for each fuel. Ethanol, n-propanol, isopropanol, and sec-butanol all showed promising performance and are great candidates to be combined with an advanced high-dilution SI strategy to enable high-dilution SI with a carbon-neutral fuel.

Thermal barrier coatings (TBCs) have been investigated both experimentally and through simulation for mixing controlled combustion (MCC) concepts as a method for reducing heat transfer losses and increasing cycle efficiency, but it is still a very active research area. Early studies were inconclusive, with different groups discovering obstacles to realizing the theoretical potential. Nuanced papers have shown that coating material properties, thickness, microstructure, and surface morphology/roughness all can impact the efficacy of the thermal barrier coating and must be accounted for. Adding to the complexities, a strong spatial and temporal heat flux inhomogeneity exists for mixing controlled combustion (diesel) imposed onto the surfaces from the impinging flame jets. In support of the United States Department of Energy SuperTruck II program goal to achieve 55% brake thermal efficiency on a heavy-duty diesel engines, this study sought to develop a deeper insight into the inhomogeneous heat flux from mixing controlled combustion on thermal barrier coatings and to infer concrete guidance for designing coatings. To that end, a co-simulation approach was developed that couples high-fidelity computational fluid dynamics (CFD) modeling of in-cylinder processes and combustion, and finite element analysis (FEA) modeling of the thermal barrier-coated and metal engine components to resolve spatial and temporal thermal boundary conditions. The models interface at the surface of the combustion chamber; FEA modeling predicts the spatially resolved surface temperature profile, while CFD develops insights into the effect of the thermal barrier coating on the combustion process and the boundary conditions on the gas side. The paper demonstrates the capability of the framework to estimate cycle impacts of the temperature swing at the surface, as well as identify critical locations on the piston/thermal barrier coating that exhibit the highest charge temperature and highest heat fluxes. In addition, the FEA results include predictions of thermal stresses, thus enabling insight into factors affecting coating durability. An example of the capability of the framework is provided to illustrate its use for investigating novel coatings and provide deeper insights to guide future coating design.

Wet ethanol is a biofuel with unique fuel properties: a high latent heat of vaporization and low equivalence ratio sensitivity. These two fuel properties enable control over the heat release process in low temperature combustion through the enhancement of in-cylinder thermal stratification. In this work, it is shown that the direct injection of wet ethanol 80 (80% ethanol, 20% water, by mass) during the intake stroke on a mid-compression ratio engine with a side-mounted gasoline direct injector does not fully premix with incoming air, leaving stratification in the cylinder which elongates the combustion process, enabling high-load low temperature combustion without engine-damaging knock. As a result, the load under naturally aspirated conditions was only limited by oxygen content as the global equivalence ratio approached stoichiometry. The results show that swirl can not only modulate the induced stratification effectively by increasing the amount of bulk motion in the cylinder but also cause a thermal efficiency penalty, since swirl increases heat transfer losses. Modulation over the induced stratification can be achieved without an efficiency penalty by employing either a dual injector system where a fraction of the total fuel is injected into the port or a split injection strategy where a fraction of the total fuel is injected during the compression stroke. This strategy enables high-load low temperature combustion, while reducing the number of regions that form NO_x and avoiding excessively rich regions that contribute to combustion inefficiency.

In-cylinder surface temperature is of heightened importance for Homogeneous Charge Compression Ignition (HCCI) combustion since the combustion mechanism is thermo-kinetically driven. Thermal Barrier Coatings (TBCs) selectively manipulate the in-cylinder surface temperature, providing an avenue for improving thermal and combustion efficiency. A surface temperature swing during combustion/expansion reduces heat transfer losses, leading to more complete combustion and reduced emissions. At the same time, achieving a highly dynamic response sidesteps preheating of charge during intake and eliminates the volumetric efficiency penalty. The magnitude and temporal profile of the dynamic surface temperature swing is affected by the TBC material properties, thickness, morphology, engine speed, and heat flux from the combustion process. This study follows prior work of authors with Yttria Stabilized Zirconia, which systematically engineered coatings for HCCI combustion. Herein, a modeling study was used to assess the impacts of various TBC material properties, e.g. density, thickness, and thermal conductivity on the temperature swing effect. Reducing conductivity emerged as a most promising avenue, rather than reducing both the density and effective conductivity by increasing porosity, the current work emphasizes a material with natively low conductivity. A novel TBC formulation was developed, leverages a class of materials that, to the author’s best knowledge, have not been used as a thermal barrier coating previously. A systematic experimental investigation was carried out using single-cylinder research engine. Experimental engine studies utilizing the novel ‘glassy’ low-K coating exhibit advanced ignition phasing and reduced combustion duration relative to the baseline engine. Heat transfer measurements indicate a net reduction in heat flux over the entire cycle, although main effect is felt during expansion, and the reduced heat transfer losses manifest in higher gross indicated thermal efficiency by approximately 5-6% on a relative basis.

Gasoline particulate filters (GPFs) are the most promising and practically applicable devices to reduce Particulate Matter (PM) and Particulate Number (PN) emissions from gasoline direct ignition engines. A model that can predict internal GPF temperature dynamics during regeneration events can then be implemented online to maintain GPF health and aide in exotherm control algorithms without the associated instrumentation costs. This work demonstrates a control-oriented model, which captures the thermal dynamics in a catalyzed, ceria-coated GPF in the axial direction. The model utilizes soot oxidation reaction kinetics to predict internal GPF temperature dynamics during regeneration events using three finite volume cells. A model methodology initially proposed by Arunachalam et al [18] is utilized with the GPF of this work, validating the broad applicability of that methodology. Then, the model’s temperature prediction fidelity is improved through axial discretization. The zonal model parameters are identified via a Particle Swarm Optimization using experimental results from the instrumented GPF. Identified parameters from the various data sets are used to develop a linear parameter varying model for prediction of the axial temperature distribution within the GPF. The resulting model is then validated against an experimental data set utilizing the exhaust temperature entering the GPF. The spatial discretization methodology employed both enables the prediction of spatial temperature variation within the GPF and improves the accuracy of the peak temperature prediction by a factor ranging from 2–10x.