Search Results

The purpose of this research is to develop a prediction technique that can be used in the development of port fuel-injection (hereinafter called PFI) gasoline engines, especially for general purpose small utility engines. Utility engines have two contradictory desirable aspects: compactness and high-power at wide open throttle. Therefore, applying the port fuel injector to utility engines presents a unique intractableness that is different from application to automobiles or motorcycles. At the condition of wide open throttle, a large amount of fuel is required to output high power, and injected fuel is deposited as a wall film on the intake port wall. Despite the fuel rich condition, emissions are required to be kept under a certain level. Thus, it is significant to understand the wall film phenomenon and control film thickness in the intake ports.

Many recent studies have shown that the Reactivity Controlled Compression Ignition (RCCI) combustion strategy can achieve high efficiency with low emissions. However, it has also been revealed that RCCI combustion is difficult at high loads due to its premixed nature. To operate at moderate to high loads with gasoline/diesel dual fuel, high amounts of EGR or an ultra low compression ratio have shown to be required. Considering that both of these approaches inherently lower thermodynamic efficiency, in this study natural gas was utilized as a replacement for gasoline as the low-reactivity fuel. Due to the lower reactivity (i.e., higher octane number) of natural gas compared to gasoline, it was hypothesized to be a better fuel for RCCI combustion, in which a large reactivity gradient between the two fuels is beneficial in controlling the maximum pressure rise rate.

The use of a hydraulic drive system with accumulator energy storage has the potential of providing large gains in fuel economy of internal combustion engine passenger automobiles. The improvement occurs because of efficient regenerative braking and the practicality of decoupling the engine operation from the driving cycle demands. The concept under study uses an engine-driven pump supplying hydraulic power to individual wheel pump/motors (P/M's) and/or an accumulator. Available P/M's have high efficiencies (e.g., 95%) at the ideal point of operation, but the efficiency falls off considerably at combinations of pressure, speed, and displacement that are significantly away from ideal. In order to maximize the fuel economy of the automobile, it is necessary to provide the proper combination of components, system design, and control policies that operate the wheel P/M's as close as possible to their maximum efficiency under all types of driving and braking conditions.

The University of Wisconsin-Madison Snowmobile Team designed and constructed a hybrid-electric snowmobile for the 2005 Society of Automotive Engineers' Clean Snowmobile Challenge. Built on a 2003 cross-country touring chassis, this machine features a 784 cc fuel-injected four-stroke engine in parallel with a 48 V electric golf cart motor. The 12 kg electric motor increases powertrain torque up to 25% during acceleration and recharges the snowmobile's battery pack during steady-state operation. Air pollution from the gasoline engine is reduced to levels far below current best available technology in the snowmobile industry. The four-stroke engine's closed-loop EFI system maintains stoichiometric combustion while dual three-way catalysts reduce NOx, HC and CO emissions by up to 94% from stock. In addition to the use of three way catalysts, the fuel injection strategy has been modified to further reduce engine emissions from the levels measured in the CSC 2004 competition.

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.

The fuel film thickness resulting from diesel fuel spray impingement was measured in a chamber at conditions representative of early injection timings used for low temperature diesel combustion. The adhered fuel volume and the radial distribution of the film thickness are presented. Fuel was injected normal to the impingement surface at ambient temperatures of 353 K, 426 K and 500 K, with densities of 10 kg/m3 and 25 kg/m3. Two injectors, with nozzle diameters of 100 μm and 120 μm, were investigated. The results show that the fuel film volume was strongly affected by the ambient temperature, but was minimally affected by the ambient density. The peak fuel film thickness and the film radius were found to increase with decreased temperature. The fuel film was found to be circular in shape, with an inner region of nearly constant thickness. The major difference observed with temperature was a decrease in the radial extent of the film.

The University of Wisconsin - Madison Hybrid Vehicle Team has designed, fabricated, tested and optimized a four-wheel drive, charge sustaining, split-parallel hybrid-electric crossover vehicle for entry into the 2006 Challenge X competition. This multi-year project is based on a 2005 Chevrolet Equinox platform. Trade-offs in fuel economy, greenhouse gas impact (GHGI), acceleration, component packaging and consumer acceptability were weighed to establish Wisconsin's Vehicle Technical Specifications (VTS). Wisconsin's Equinox, nicknamed the Moovada, utilizes a General Motors (GM) 110 kW 1.9 L CIDI engine coupled to GM's 6-speed F40 transmission. The rear axle is powered by a 65 kW Ballard induction motor/gearbox powered from a 44-module (317 volts nominal) Johnson Controls Inc., nickel-metal hydride hybrid battery pack. It includes a newly developed proprietary battery management algorithm which broadcasts the battery's state of charge onto the CAN network.

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.

In the current investigation, the authors identified conditions under which increased in-cylinder turbulence can be used to improve diesel emissions. Two separate regimes of engine operation were identified; one in which combustion was constrained by mixing and one in which it was not. These regimes were dubbed under-mixed and over-mixed, respectively. It was found that increasing mixing in the former regime had a profound effect on soot emission. Fuel injection characteristics were found to be extremely important in determining the point at which mixing became inadequate. In addition, the ratio of the fuel injection momentum flux relative to that of the gas injection was found to be important in determining how increasing mixing would effect soot emissions.

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.

Neural networks have been used for engine computations in the recent past. One reason for using neural networks is to capture the accuracy of multi-dimensional CFD calculations or experimental data while saving computational time, so that system simulations can be performed within a reasonable time frame. This paper describes three methods to improve upon neural network predictions. Improvement is demonstrated for in-cylinder pressure predictions in particular. The first method incorporates a physical combustion model within the transfer function of the neural network, so that the network predictions incorporate physical relationships as well as mathematical models to fit the data. The second method shows how partitioning the data into different regimes based on different physical processes, and training different networks for different regimes, improves the accuracy of predictions.

This research explored methods to reduce regulated emissions in a small-bore, direct-injection diesel engine. Swirl was used to influence mixing of the spray plumes, and alternative fuels were used to study the effects of oxygenated and water microemulsion diesel fuels on emissions. Air/fuel mixing enhancement was achieved in the running engine by blocking off a percentage of one of the two intake ports. The swirl was characterized at steady-state conditions with a flowbench and swirl meter. Swirl ratios of 1.85, 2.70, and 3.29 were studied in the engine tests at full load with engine speeds of 1303, 1757, and 1906 rev/min. Increased swirl was shown to have negative effects on emissions due to plume-to-plume interactions. Blends of No. 2 diesel and biodiesel were used to investigate the presence of oxygen in the fuel and its effects on regulated emissions. Pure No. 2 diesel fuel, a 15% and a 30% biodiesel blend (by weight) were used.

We have developed a methodology for predicting combustion and emissions in a Homogeneous Charge Compression Ignition (HCCI) Engine. The methodology judiciously uses a fluid mechanics code followed by a chemical kinetics code to achieve great reduction in the computational requirements; to a level that can be handled with current computers. In previous papers, our sequential, multi-zone methodology has been applied to HCCI combustion of short-chain hydrocarbons (natural gas and propane). Applying the same procedure to long-chain hydrocarbons (iso-octane) results in unacceptably long computational time. In this paper, we show how the computational time can be made acceptable by developing a segregated solver. This reduces the run time of a ten-zone problem by an order of magnitude and thus makes it much more practical to make combustion studies of long-chain hydrocarbons.

A direct injection-gasoline (DI-G) system was applied to a heavy-duty diesel-type engine to study the effects of charge stratification on the performance of premixed compression ignited combustion. The effects of the fuel injection parameters on combustion phasing were of primary interest. The simultaneous effects of the fuel stratification on Unburned Hydrocarbon (UHC), Oxides of Nitrogen (NOx), Carbon Monoxide (CO), and smoke emissions were also measured. Engine tests were conducted with altered injection parameters covering the entire load range of normally aspirated Homogeneous Charge Compression Ignited (HCCI) combustion. Combustion phasing tests were also conducted at several engine speeds to evaluate its effects on a fuel stratification strategy.

The Diesel engine is a commercially attractive powerplant, however it is noted to have significant specific output of harmful emissions under some operating conditions. One possible solution for reduction of the harmful emissions from the Diesel engine is greater control over the fuel injection event. To gain further understanding of liquid phase Diesel fuel injection spray characteristics, a 2.44 liter displacement, 4 stroke engine was modified for optical access and fitted with a Caterpillar Hydraulic Electronic Unit Injection (HEUI) system. The data collection system consisted of a high repetition rate diode pumped Nd:YAG laser frequency doubled to 532 nm for visible illumination and a Kodak High Speed Motion Analyzer for recording fuel spray images. The engine was motored under various inlet conditions to create an engine combustion chamber environment typical of those found in commercial engines of similar per cylinder displacement class.

An experimental study was carried out to investigate the effects of fuel injection timing on detailed chemical composition and size distributions of diesel particulate matter (PM) and regulated gaseous emissions in a modern heavy-duty D.I. diesel engine. These measurements were made for two different diesel fuels: No. 2 diesel (Fuel A) and ultra low sulfur diesel (Fuel B). A single-cylinder 2.3-liter D.I. diesel engine equipped with an electronically controlled unit injection system was used in the experiments. PM measurements were made with an enhanced full-dilution tunnel system at the Engine Research Center (ERC) of the University of Wisconsin-Madison (UW-Madison) [1, 2]. The engine was run under 2 selected modes (25% and 75% loads at 1200 rpm) of the California Air Resources Board (CARB) 8-mode test cycle.

In a recent study, quantitative measurements were presented of in-cylinder spatial distributions of mixture equivalence ratio in a single-cylinder light-duty optical diesel engine, operated with a non-reactive mixture at conditions similar to an early injection low-temperature combustion mode. In the experiments a planar laser-induced fluorescence (PLIF) methodology was used to obtain local mixture equivalence ratio values based on a diesel fuel surrogate (75% n-heptane, 25% iso-octane), with a small fraction of toluene as fluorescing tracer (0.5% by mass). Significant changes in the mixture's structure and composition at the walls were observed due to increased charge motion at high swirl and injection pressure levels. This suggested a non-negligible impact on wall heat transfer and, ultimately, on efficiency and engine-out emissions.

A fundamentally based quasi-dimensional NOx emission model for spark ignition direct injection (SIDI) gasoline engines was developed. The NOx model consists of a chemical mechanism and three sub-models. The classical extended Zeldovich mechanism and N₂O pathway for NOx formation mechanism were employed as the chemical mechanism in the model. A characteristic time model for the radical species H, O and OH was incorporated to account for non-equilibrium of radical species during combustion. A model of homogeneity which correlates fundamental dimensionless numbers and mixing time was developed to model the air-fuel mixing and inhomogeneity of the charge. Since temperature has a dominant effect on NOx emission, a flame temperature correlation was developed to model the flame temperature during the combustion for NOx calculation. Measured NOx emission data from a single-cylinder SIDI research engine at different operating conditions was used to validate the NOx model.

Engine-out CO emission and fuel conversion efficiency were measured in a highly-dilute, low-temperature diesel combustion regime over a swirl ratio range of 1.44-7.12 and a wide range of injection timing. At fixed injection timing, an optimal swirl ratio for minimum CO emission and fuel consumption was found. At fixed swirl ratio, CO emission and fuel consumption generally decreased as injection timing was advanced. Moreover, a sudden decrease in CO emission was observed at early injection timings. Multi-dimensional numerical simulations, pressure-based measurements of ignition delay and apparent heat release, estimates of peak flame temperature, imaging of natural combustion luminosity and spray/wall interactions, and Laser Doppler Velocimeter (LDV) measurements of in-cylinder turbulence levels are employed to clarify the sources of the observed behavior.

A new spray model has been developed to improve the prediction of diesel engine combustion and emissions using the KIVA-II CFD code. The accuracy of modeling the spray breakup process has been improved by the inclusion of Rayleigh-Taylor accelerative instabilities, which are calculated simultaneously with a Kelvin-Helmholtz wave model. This model improves the prediction of the droplet sizes within a diesel spray and provides a more accurate initial condition for the evaporation, combustion, and emissions models. An improvement to the droplet drag model is also presented. This model accounts for the increased droplet drag due to the change in the droplet's shape, as well as the increase in the frontal area of the droplet. The drag model affects the breakup process locally, producing a more realistic droplet size distribution, and therefore a more accurate calculation of the vaporization process.