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An investigation of high speed direct injection (DI) compression ignition (CI) engine combustion fueled with gasoline injected using a triple-pulse strategy in the low temperature combustion (LTC) regime is presented. This work aims to extend the operation ranges for a light-duty diesel engine, operating on gasoline, that have been identified in previous work via extended controllability of the injection process. The single-cylinder engine (SCE) was operated at full load (16 bar IMEP, 2500 rev/min) and computational simulations of the in-cylinder processes were performed using a multi-dimensional CFD code, KIVA-ERC-Chemkin, that features improved sub-models and the Chemkin library. The oxidation chemistry of the fuel was calculated using a reduced mechanism for primary reference fuel combustion chosen to match ignition characteristics of the gasoline fuel used for the SCE experiments.

There is significant potential for connected and autonomous vehicles to impact vehicle efficiency, fuel economy, and emissions, especially for hybrid-electric vehicles. These improvements could have large-scale impact on oil consumption and air-quality if deployed in large Mobility-as-a-Service or ride-sharing fleets. As part of the US Department of Energy's current Advanced Vehicle Technology Competition (AVCT), EcoCAR: The Mobility Challenge, Mississippi State University’s EcoCAR Team is redesigning and doing the development work necessary to convert a conventional gasoline spark-ignited 2019 Chevy Blazer into a hybrid-electric vehicle with SAE Level 2 autonomy. The target consumer segments for this effort are the Mobility-as-a-Service fleet owners, operators and riders. To accomplish this conversion, the MSU team is implementing a P4 mild hybridization strategy that is expected to result in a 30% increase in fuel economy over the stock Blazer.

A modular and scalable Dense Medium Plasma Water Purification Reactor was developed, which uses atmospheric-pressure electrical discharges under water to generate highly reactive species to break down organic contaminants and microorganisms. Key benefits of this novel technology include: (i) extremely high efficiency in both decontamination and disinfection; (ii) operating continuously at ambient temperature and pressure; (iii) reducing demands on the containment vessel; and (iv) requiring no consumables. This plasma based technology was developed to replace the catalytic reactor being used in the planned International Space Station Water Processor Assembly.

A previously developed CFD-based optimization tool is utilized to find optimal engine operating conditions with respect to fuel consumption and emissions. The optimization algorithm employed is based on the steepest descent method where an adaptive cost function is minimized along each line search using an effective backtracking strategy. The adaptive cost function is based on the penalty method, where the penalty coefficient is increased after every line search. The parameter space is normalized and, thus, the optimization occurs over the unit cube in higher-dimensional space. The application of this optimization tool is demonstrated for the Sulzer S20, a central-injection, non-road DI diesel engine. The optimization parameters are the start of injection of the two pulses of a split injection system, the duration of each pulse, the exhaust gas recirculation rate, the boost pressure and the compression ratio.

A global optimization method has been developed for an engine simulation code and utilized in the search of optimal fuel injection strategies. This method uses a Lagrange interpolation function which interpolates engine output data generated at the vertices and the intermediate points of the input parameters. This interpolation function is then used to find a global minimum over the entire parameter set, which in turn becomes the starting point of a CFD-based optimization. The CFD optimization is based on a steepest descent method with an adaptive cost function, where the line searches are performed with a fast-converging backtracking algorithm. The adaptive cost function is based on the penalty method, where the penalty coefficient is increased after every line search. The parameter space is normalized and, thus, the optimization occurs over the unit cube in higher-dimensional space.

Optimal fuel injection strategies are obtained with a micro-genetic algorithm and an adaptive gradient method for a nonroad, medium-speed DI diesel engine equipped with a multi-orifice, asynchronous fuel injection system. The gradient optimization utilizes a fast-converging backtracking algorithm and an adaptive cost function which is based on the penalty method, where the penalty coefficient is increased after every line search. The micro-genetic algorithm uses parameter combinations of the best two individuals in each generation until a local convergence is achieved, and then generates a random population to continue the global search. The optimizations have been performed for a two pulse fuel injection strategy where the optimization parameters are the injection timings and the nozzle orifice diameters.

Neural networks are useful tools for optimization studies since they are very fast, so that while capturing the accuracy of multi-dimensional CFD calculations or experimental data, they can be run numerous times as required by many optimization techniques. This paper describes how a set of neural networks trained on a multi-dimensional CFD code to predict pressure, temperature, heat flux, torque and emissions, have been used by a genetic algorithm in combination with a hill-climbing type algorithm to optimize operating parameters of a diesel engine over the entire speed-torque map of the engine. The optimized parameters are mass of fuel injected per cycle, shape of the injection profile for dual split injection, start of injection, EGR level and boost pressure. These have been optimized for minimum emissions. Another set of neural networks have been trained to predict the optimized parameters, based on the speed-torque point of the engine.

A study of the combined use of split injections, EGR, and flexible boosting was conducted. Statistical optimization of the engine operating parameters was accomplished using a new response surface method. The objective of the study was to demonstrate the emissions and fuel consumption capabilities of a state-of-the-art heavy -duty diesel engine when using split injections, EGR, and flexible boosting over a wide range of engine operating conditions. Previous studies have indicated that multiple injections with EGR can provide substantial simultaneous reductions in emissions of particulate and NOx from heavy-duty diesel engines, but careful optimization of the operating parameters is necessary in order to receive the full benefit of these combustion control techniques. Similarly, boost has been shown to be an important parameter to optimize. During the experiments, an instrumented single-cylinder heavy -duty diesel engine was used.

Diesel engine in-cylinder combustion processes have been studied using computational models with particular attention to spray development, vaporization, fuel/air mixture formation and combustion. A thermodynamic zero-dimensional cycle analysis program was used to determine initial conditions for the multidimensional calculations. A modified version of the time-dependent, three-dimensional computational fluid dynamics code KIVA-II was used for the computations, with a detailed treatment for the spray calculations and a simplified model for combustion. The calculations were used to obtain an understanding of the potential predictive capabilities of the models. It was found that there is a strong sensitivity of the results to numerical grid resolution. With proper grid resolution, the calculations were found to reproduce experimental data for non- vaporizing and vaporizing sprays. However, for vaporizing sprays with combustion, extremely fine grids are needed.

The three-dimensional KIVA code has been used to study the effects of injection pressure and split injections on diesel engine performance and soot and NOx emissions. The code has been updated with state-of-the-art submodels including: a wave breakup atomization model, drop drag with drop distortion, spray/wall interaction with sliding, rebounding, and breaking-up drops, multistep kinetics ignition and laminar-turbulent characteristic time combustion, wall heat transfer with unsteadiness and compressibility, Zeldovich NOx formation, and soot formation with Nagle Strickland-Constable oxidation. The computational results are compared with experimental data from a single-cylinder Caterpillar research engine equipped with a high-pressure, electronically-controlled fuel injection system, a full-dilution tunnel for soot measurements, and gaseous emissions instrumentation.

The development of analytic models of diesel engine flow, combustion and subprocesses is described. The models are intended for use as design tools by industry for the prediction of engine performance and emissions to help reduce engine development time and costs. Part of the research program includes performing engine experiments to provide validation data for the models. The experiments are performed on a single-cylinder version of the Caterpillar 3406 engine that is equipped with state-of-the-art high pressure electronic fuel injection and emissions instrumentation. In-cylinder gas velocity and gas temperature measurements have also been made to characterize the flows in the engine.

A transmission system model for Ford Motor Company's automatic transmission (AOD) system used in the Lincoln Town Car has been developed using the free-body diagram method (Newtonian approach). This model is sophisticated enough to represent the dynamic behavior of the transmission system, yet simple enough to use as a real time computer simulation tool, and as an embedded model within a dynamic observer. The transmission system and torque converter models presented in this paper are part of a larger powertrain system model at the Powertrain Control Research Laboratory, University of Wisconsin-Madison.

Progress on the development and validation of a CFD model for diesel engine combustion and flow is described. A modified version of the KIVA code is used for the computations, with improved submodels for liquid breakup, drop distortion and drag, spray/wall impingement with rebounding, sliding and breaking-up drops, wall heat transfer with unsteadiness and compressibility, multistep kinetics ignition and laminar-turbulent characteristic time combustion models, Zeldovich NOx formation, and soot formation with Nagle Strickland-Constable oxidation. The code also considers piston-cylinder-liner crevice flows and allows computations of the intake flow process in the realistic engine geometry with two moving intake valves. Significant progress has been made using a modified RNG k-ε turbulence model, and a multicomponent fuel vaporization model and a flamelet combustion model have been implemented.

An integrated numerical model has been developed for diesel engine computations based on the KIVA-II code. The model incorporates a modified RNG k-ε, turbulence model, a ‘wave’ breakup spray model, the Shell ignition model, the laminar-and-turbulent characteristic-time combustion model, a crevice flow model, a spray/wall impingement model that includes rebounding and breaking-up drops, and other improved submodels in the KIVA code. The model was validated and applied to model successfully different types of diesel engines under various operating conditions. These engines include a Caterpillar engine with different injection pressures at different injection timings, a small Tacom engine at different loads, and a Cummins engine modified by Sandia for optical experiments. Good levels of agreement in cylinder pressures and heat release rate data were obtained using the same computer model for all engine cases.

Variations in the in cylinder flow field which result from differences in the intake flow are known to have important effects on the performance and emissions behavior of diesel engines. The intake flow and combustion in a heavy duty DI diesel engine with a dual valve port have been simulated using the computational fluid dynamics code KIVA-3. Variation of the in-cylinder flow field has been achieved by varying the intake valve timing. Variations in the in-cylinder flow, including a range of length scales, degrees of inhomogeneity in a number of scalar and vector quantities, and the persistence of various flow structures, are compared, and their significance to combustion and emissions parameters are assessed. The interaction of fuel spray parameters, particularly spray-wall interaction with structures present in the flow field are evaluated.

A computer model developed for describing multicomponent fuel vaporization, and ignition in diesel engines has been applied in this study to understand cold-starting and the parameters that are of significant influence on this phenomena. This research utilizes recent improvements in spray vaporization and combustion models that have been implemented in the KIVA-II CFD code. Typical engine fuels are blends of various fuels species, i.e., multicomponent. Thus, the original single component fuel vaporization model in KIVA-II was replaced by a multicomponent fuel vaporization model (based on the model suggested by Jin and Borman). The modelhas been extended to model diesel sprays under typical diesel conditions, including the effect of fuel cetane number variation. Necessary modifications were carried out in the atomization and collision sub-models. The ignition model was also modified to account for fuel composition effects by modifying the Shell ignition model.

An engine emissions and performance study was conducted in conjunction with a series of experiments using a constant volume cold spray chamber. The purpose of the study was to explore the effects of number of holes and hole size on the emissions and performance of a direct injection heavy duty diesel engine. The spray experiments provide insight into the spray parameters and their role in the engine's combustion processes. The fuel system used for both the engine and spray chamber experiments was an electronically controlled, common rail injector. The injector nozzle hole size and number combinations used in the experiments included 225X8 (225 gm diameter holes with 8 holes in the nozzle), 260X6, 260X8, and 30OX6. The engine tests were conducted on an instrumented single cylinder version of the Caterpillar 3400 series heavy duty diesel engine. Data were taken with the engine running at 1600 RPM, 75% load.

This research uses computational modeling to explore methods to increase diesel engine power density while maintaining low pollutant emission levels. Previous experimental studies have shown that injection-rate profiles and injector configurations play important roles on the performance and emissions of particulate and NOx in DI diesel engines. However, there is a lack of systematic studies and fundamental understanding of the mechanisms of spray atomization, mixture formation and distribution, and subsequently, the combustion processes in spray/spray and spray/swirl interaction and flow configurations. In this study, the effects of split injections and multiple injector configurations on diesel engine emissions are investigated numerically using a multidimensional computer code. In order to be able to explore the effects of enhanced fuel-air mixing, the use of multiple injectors with different injector locations, spray orientations and impingement angles was studied.

Two soot-containing turbulent non-premixed flames burning gaseous acetylene in atmospheric-pressure air were investigated by conducting non-intrusive optical experiments at various flame locations. The differences in burner exit Reynolds numbers of these flames were large enough to examine the influence of flow dynamics on soot formation and evolution processes in heavily-sooting flames. By accounting for the fractal nature of aggregated primary particles (spherules), the proper interpretation of the laser scattering and extinction measurements yielded all the soot parameters of principal interest. With the separation of spherule and aggregate sizes, the axial zones of the prevailing turbulent soot mechanisms were accurately identified. With the high propensity of acetylene fuel to soot, relatively fast particle nucleation process led to high concentrations immediately above the burner exit.

A numerical simulation and optimization study was conducted for a medium speed direct injection diesel engine. The engine's operating characteristics were first matched to available experimental data to test the validity of the numerical model. The KIVA-3V ERC CFD code was then modified to allow independent spray events from two rows of nozzle holes. The angular alignment, nozzle hole size, and injection pressure of each set of nozzle holes were optimized using a micro-genetic algorithm. The design fitness criteria were based on a multi-variable merit function with inputs of emissions of soot, NOx, unburned hydrocarbons, and fuel consumption targets. Penalties to the merit function value were used to limit the maximum in-cylinder pressure and the burned gas temperature at exhaust valve opening. The optimization produced a 28.4% decrease in NOx and a 40% decrease in soot from the baseline case, while giving a 3.1% improvement in fuel economy.