Search Results

Reactivity Controlled Compression Ignition (RCCI) is an engine combustion strategy that utilizes in-cylinder fuel blending to produce low NOx and PM emissions while maintaining high thermal efficiency. Previous RCCI research has been investigated in single-cylinder heavy-duty engines [1, 2, 3, 4, 5, 6]. The current study investigates RCCI operation in a light-duty multi-cylinder engine over a wide number of operating points representing vehicle operation over the US EPA FTP test. Similarly, previous RCCI engine experiments have used petroleum based fuels such as ultra-low sulfur diesel fuel (ULSD) and gasoline, with some work done using high percentages of biofuels, namely E85 [7]. The current study was conducted to examine RCCI performance with moderate biofuel blends, such as E20 and B20, as compared to conventional gasoline and ULSD.

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 focus of this paper is to discuss the modeling and control of intake plenum pressure on the Powertrain Control Research Laboratory's (PCRL) Single-Cylinder Engine (SCE) transient test system using a patented device known as the Intake Air Simulator (IAS), which dynamically controls the intake plenum pressure, and, subsequently, the instantaneous airflow into the cylinder. The IAS exists as just one of many devices that the PCRL uses to control the dynamic boundary conditions of its SCE transient test system to make it “think” and operate as though it were part of a Multi-Cylinder Engine (MCE) test system. The model described in this paper will be used to design a second generation of this device that utilizes both continuously and discretely actuating valves working in parallel.

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.

A direct calibration has been performed on laser-induced fluorescence measurements of the oil film in a single cylinder air-cooled research engine by simultaneously measuring the minimum oil film thickness by the capacitance technique. At the minimum oil film thickness the capacitance technique provides an accurate measure of the ring-wall distance, and this value is used as a reference for the photomultiplier voltage, giving a calibration coefficient. This calibration coefficient directly accounts for the effect of temperature on the fluorescent properties of the constituents of the oil which are photoactive. The inability to accurately know the temperature of the oil has limited the utility of off-engine calibration techniques. Data are presented for the engine under motoring conditions at speeds from 800 - 2400 rpm and under varying throttle positions.

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 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.

The demand for highly flexible manipulation of plant growth generations, modification of specific plant processes, and genetically engineered crop varieties in a controlled environment has led to the development of a Commercial Plant Biotechnology Facility (CPBF). The CPBF is a quad-middeck locker playload to be mounted in the EXPRESS Rack that will be installed in the International Space Station (ISS). The CPBF integrates proven ASTROCULTURE” technologies, state-of-the-art control software, and fault tolerance and recovery technologies together to increase overall system efficiency, reliability, robustness, flexibility, and user friendliness. The CPBF provides a large plant growing volume for the support of commercial plant biotechnology studies and/or applications for long time plant research in a reduced gravity environment.

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.

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 comprehensive biodiesel combustion model is presented for use in multi-dimensional engine simulations. The model incorporates realistic physical properties in a vaporization model developed for multi-component fuel sprays and applies an improved mechanism for biodiesel combustion chemistry. Previously, a detailed mechanism for methyl decanoate and methyl-9-decenoate was reduced from 3299 species to 85 species to represent the components of biodiesel fuel. In this work, a second reduction was performed to further reduce the mechanism to 69 species. Steady and unsteady spray simulations confirmed that the model adequately reproduced liquid penetration observed in biodiesel spray experiments. Additionally, the new model was able to capture expected fuel composition effects with low-volatility components and fuel blend sprays penetrating further.

Fuel-borne catalysts (FBC) have demonstrated efficacy as an important strategy for integrated diesel emission control. The research summarized herein provides new methodologies for the characterization of engine-out speciated emissions. These analytical tools provide new insights on the mode of action and chemical forms of metal emissions arising from use of a platinum and cerium based commercial FBC, both with and without a catalyzed diesel particulate filter. Characterization efforts addressed metal solubility (water, methanol and dichloromethane) and particle size and charge of the target species in the water and solvent extracts. Platinum and cerium species were quantified using state-of-the-art high resolution plasma mass spectrometry. Liquid-chromatography-triple quad mass spectrometry techniques were developed to quantify potential parent Pt-FBC in the PM extracts. Speciation was examined for emissions from cold and warm engine cycles collected from an engine dynamometer.

A hydrostatic dynamometer capable of accurately controlling the speed and torque of an engine has been designed and constructed. The thrust of this work is not only to build a better dynamometer, it is the first step in creating a system for laboratory simulation of the actual load environment of engines and powertrains. This paper presents the design, construction, and evaluation of a hydrostatic dynamometer. The evaluation includes speed and torque limits, and bandwidth of the dynamometer. Also, the dynamometer is compared with those in common use, and the feasibility of accurately reproducing the engine or powertrain load environments are assessed. This is the first phase of a development program; future research is discussed.

Brake systems in current production automobiles are the result of a long evolutionary process beginning with the first practical hydraulic brake patent in 1917. While the basic hydraulic design has many advantages, recent modifications to this system for anti-lock braking and traction control considerably increase the cost of manufacture. As a result, many manufacturers are investigating the possibility of developing alternate braking system structures that cost less and can easily interface with vehicle electronics. Evaluating these systems for fault tolerance and failure effects is crucial to provide a safe and reliable vehicle braking system. This paper demonstrates the use of the Fault Tree Analysis method for carrying out such an evaluation. An example system is presented to illustrate the application of this method to automobile brake design.

Combustion under stratified operating conditions in a direct-injection spark-ignition engine was investigated using simultaneous planar laser-induced fluorescence imaging of the fuel distribution (via 3-pentanone doped into the fuel) and the combustion products (via OH, which occurs naturally). The simultaneous images allow direct determination of the flame front location under highly stratified conditions where the flame, or product, location is not uniquely identified by the absence of fuel. The 3-pentanone images were quantified, and an edge detection algorithm was developed and applied to the OH data to identify the flame front position. The result was the compilation of local flame-front equivalence ratio probability density functions (PDFs) for engine operating conditions at 600 and 1200 rpm and engine loads varying from equivalence ratios of 0.89 to 0.32 with an unthrottled intake. Homogeneous conditions were used to verify the integrity of the method.

The ASTROCULTURE™ (ASC) middeck flight experiment series was developed to test subsystems required to grow plants in reduced gravity, with the goal of developing a plant growth unit suitable for conducting quality biological research in microgravity. Previous Space Shuttle flights (STS-50 and STS-57) have successfully demonstrated the ability to control water movement through a particulate rooting matrix in microgravity and the ability of LED lighting systems to provide high levels of irradiance without excessive heat build-up in microgravity. The humidity and temperature control system used in the middeck flight unit is described in this paper. The system controls air flow and provides dehumidification, humidification, and condensate recovery for a plant growth chamber volume of 1450 cm3.

Automatic manufacturability analysis of injection moldings, sheet metal castings, stampings, forgings, etc., using knowledge-based heuristics depends on shape features, which are abstractions of the three dimensional (3D) geometric model of the parts. Conventional CAD systems do not explicitly contain shape feature information, therefore such information needs to be extracted from them. So far, extraction of shape features has been restricted to models with simple geometric shapes such as planar, cylindrical or conical shapes. Extending shape feature extraction to non-linear geometric models will allow Design For Manufacturability (DFM) analysis of non-linear models. This paper presents an approach to extract features from non-linear geometric models. The approach is based on abstract geometric entities called C-loops. The formation of a C-loop depends on a geometric entity called a silhouette. The C-loops are derived from the silhouette boundaries of an object.