Search Results

Modeling plume interaction and collapse for direct-injection gasoline sprays is important because of its impact on fuel-air mixing and engine performance. Nevertheless, the aerodynamic interaction between plumes and the complicated two-phase coupling of the evaporating spray has shown to be notoriously difficult to predict. With the availability of high-speed (100 kHz) Particle Image Velocimetry (PIV) experimental data, we compare velocity field predictions between plumes to observe the full temporal evolution leading up to plume merging and complete spray collapse. The target “Spray G” operating conditions of the Engine Combustion Network (ECN) is the focus of the work, including parametric variations in ambient gas temperature. We apply both LES and RANS spray models in different CFD platforms, outlining features of the spray that are most critical to model in order to predict the correct aerodynamics and fuel-air mixing.

A two-stage PPCI-diffusion combustion process recently showed good potential to enable clean and fuel-efficient gasoline compression ignition (GCI) combustion at medium-to-high loads. By conducting closed-cycle 3-D CFD combustion analysis, a further step was undertaken in this work to evaluate and optimize the PPCI-diffusion combustion strategy at a full load operating point (2000rpm-23.5 bar IMEPcc) while keeping engine-out NOx below 1 g/kWh. The light-duty GCI engine used in this investigation featured a custom-designed piston bowl geometry at a 17.0 compression ratio (CR), a high pressure diesel fuel injection system, and advanced single-stage turbocharging. A split fuel injection strategy was used to enable the two-stage PPCI-diffusion combustion process. First, the injector spray pattern and swirl ratio effects were evaluated. In-cylinder air utilization and the PPCI-diffusion combustion process were notably influenced by the closed-cycle combustion system design.

Traditional Lagrangian spray modeling approaches for internal combustion engines are highly grid-dependent due to insufficient resolution in the near nozzle region. This is primarily because of inherent restrictions of volume fraction with the Lagrangian assumption together with high computational costs associated with small grid sizes. A state-of-the-art grid-convergent spray modeling approach was recently developed and implemented by Senecal et al., (ASME-ICEF2012-92043) in the CONVERGE software. The key features of the methodology include Adaptive Mesh Refinement (AMR), advanced liquid-gas momentum coupling, and improved distribution of the liquid phase, which enables use of cell sizes smaller than the nozzle diameter. This modeling approach was rigorously validated against non-evaporating, evaporating, and reacting data from the literature.

In an effort of providing better understanding of regeneration mechanisms of diesel particulate matter (PM), this experimental investigation focused on evaluating the amount of heat release generated during the thermal reaction of diesel PM and the concentrations of soluble organic compounds (SOCs) dissolved in PM emissions. Differences in oxidation behaviors were observed for two different diesel PM samples: a SOC-containing PM sample and a dry soot sample with no SOCs. Both samples were collected from a cordierite particulate filter membrane in a thermal reactor connected to the exhaust pipe of a light-duty diesel engine. A differential scanning calorimeter (DSC) and a thermogravimetric analyzer (TGA) were used to measure the amount of heat release during oxidation, along with subsequent oxidation rates and the concentrations of SOCs dissolved in particulate samples, respectively.

For several years there has been a great deal of effort made in researching ways to run a compression ignition engine with simultaneously high efficiency and low emissions. Recently much of this focus has been dedicated to using gasoline-like fuels that are more volatile and less reactive than conventional diesel fuel to allow the combustion to be more premixed. One of the key challenges to using fuels with such properties in a compression ignition engine is stable engine operation at low loads. This paper provides an analysis of how stable gasoline compression ignition (GCI) engine operation was achieved down to idle speed and load on a multi-cylinder compression ignition engine using only 87 anti-knock index (AKI) gasoline. The variables explored to extend stable engine operation to idle included: uncooled exhaust gas recirculation (EGR), injection timing, injection pressure, and injector nozzle geometry.

This paper determines the impact of ambient temperature on energy consumption of a variety of vehicles in the laboratory. Several conventional vehicles, several hybrid electric vehicles, a plug-in hybrid electric vehicle and a battery electric vehicle were tested for fuel and energy consumption under test cell conditions of 20°F, 72°F and 95°F with 850 W/m₂ of emulated radiant solar energy on the UDDS, HWFET and US06 drive cycles. At 20°F, the energy consumption increase compared to 72°F ranges from 2% to 100%. The largest increases in energy consumption occur during a cold start, when the powertrain losses are highest, but once the powertrains reach their operating temperatures, the energy consumption increases are decreased. At 95°F, the energy consumption increase ranges from 2% to 70%, and these increases are due to the extra energy required to run the air-conditioning system to maintain 72°F cabin temperatures.

Recent advances in x-ray spray diagnostics at Argonne National Laboratory's Advanced Photon Source have made absorption measurements of individual spray events possible. A focused x-ray beam (5×6 μm) enables collection of data along a single line of sight in the flow field and these measurements have allowed the calculation of quantitative, shot-to-shot statistics for the projected mass of fuel sprays. Raster scanning though the spray generates a two-dimensional field of data, which is a path integrated representation of a three-dimensional flow. In a previous work, we investigated the shot-to-shot variation over 32 events by visualizing the ensemble standard deviations throughout a two dimensional mapping of the spray. In the current work, provide further analysis of the time to steady-state and steady-state spatial location of the fluctuating field via the transverse integrated fluctuations (TIF).

This research investigates the potential of gasoline compression ignition (GCI) to achieve low engine-out NOx emissions with high fuel efficiency in a heavy-duty diesel engine. The experimental work was conducted in a model year (MY) 2013 Cummins ISX15 heavy-duty diesel engine, covering a load range of 5 to 15 bar BMEP at 1375 rpm. The engine compression ratio (CR) was reduced from the production level of 18.9 to 15.7 without altering the combustion bowl design. In this work, four gasolines with research octane number (RON) ranging from 58 to 93 were studied. Overall, GCI operation resulted in enhanced premixed combustion, improved NOx-soot tradeoffs, and similar or moderately improved fuel efficiency compared to diesel combustion. A split fuel injection strategy was employed for the two lower reactivity gasolines (RON80 and RON93), while the RON60 and RON70 gasolines used a single fuel injection strategy.

The particulate matter (PM) produced from a diesel engine-simulating combustor was characterized in its morphology, microstructure, and fractal geometry by using a unique thermophoretic sampling and Transmission Electron Microscopy (TEM) system. These results revealed that diesel PM produced from the laboratory-scale burner showed similar morphological characteristics to the particulates produced from diesel engines. The flame air/fuel ratio and the particulate temperature history have significant influences on both particle size and fractal geometry. The primary particle sizes were measured to be 14.7 nm and 14.8 nm under stoichiometric and fuel-rich flame conditions, respectively. These primary particle sizes are smaller than those produced from diesel engines. The radii of gyration for the aggregate particles were 83.8 nm and 47.5 nm under these two flame conditions.

Perception in adverse weather conditions is one of the most prominent challenges for automated driving features. The sensors used for mid-to-long range perception most impacted by weather (i.e., camera and LiDAR) are susceptible to data degradation, causing potential system failures. This research series aims to better understand sensor data degradation characteristics in real-world, dynamic environmental conditions, focusing on adverse weather. To achieve this, a dataset containing LiDAR (Velodyne VLP-16) and camera (Mako G-507) data was gathered under static scenarios using a single vehicle target to quantify the sensor detection performance. The relative position between the sensors and the target vehicle varied longitudinally and laterally. The longitudinal position was varied from 10m to 175m at 25m increments and the lateral position was adjusted by moving the sensor set angle between 0 degrees (left position), 4.5 degrees (center position), and 9 degrees (right position).

This study undertakes an investigation of the effect of battery charge balance in hybrid electric vehicles (HEVs) on EPA fuel economy label values. EPA's updated method was fully implemented in 2011 and uses equations which weight the contributions of fuel consumption results from multiple dynamometer tests to synthesize city and highway estimates that reflect average U.S. driving patterns. For the US06 and UDDS cycles, the test results used in the computation come from individual phases within the overall certification driving cycles. This methodology causes additional complexities for hybrid vehicles, because although they are required to be charge-balanced over the course of a full drive cycle, they may have net charge or discharge within the individual phases. As a result, the fuel consumption value used in the label value calculation can be skewed.

This study presents experimental and numerical examination of directly injected (DI) propane and iso-octane, surrogates for liquified petroleum gas (LPG) and gasoline, respectively, at various engine like conditions with the overall objective to establish the baseline with regards to fuel delivery required for future high efficiency DI-LPG fueled heavy-duty engines. Sprays for both iso-octane and propane were characterized and the results from the optical diagnostic techniques including high-speed Schlieren and planar Mie scattering imaging were applied to differentiate the liquid-phase regions and the bulk spray phenomenon from single plume behaviors. The experimental results, coupled with high-fidelity internal nozzle-flow simulations were then used to define best practices in CFD Lagrangian spray models.

A computational fluid dynamics (CFD) guided combustion system optimization was conducted for a heavy-duty compression-ignition engine with a gasoline-like fuel that has an anti-knock index (AKI) of 58. The primary goal was to design an optimized combustion system utilizing the high volatility and low sooting tendency of the fuel for improved fuel efficiency with minimal hardware modifications to the engine. The CFD model predictions were first validated against experimental results generated using the stock engine hardware. A comprehensive design of experiments (DoE) study was performed at different operating conditions on a world-leading supercomputer, MIRA at Argonne National Laboratory, to accelerate the development of an optimized fuel-efficiency focused design while maintaining the engine-out NOx and soot emissions levels of the baseline production engine.

Low temperature combustion engine technologies are being investigated for high efficiency and low emissions. However, such engine technologies often produce higher engine-out hydrocarbon (HC) and carbon monoxide (CO) emissions, and their operating range is limited by the fuel properties. In this study, two different fuels, a US market gasoline containing 10% ethanol (RON 92 E10) and a higher reactivity gasoline (RON 80 E0), were compared on Delphi’s second generation Gasoline Direct-Injection Compression Ignition (Gen 2.0 GDCI) multi-cylinder engine. The engine was evaluated at three operating points ranging from a light load condition (800 rpm/2 bar IMEPg) to medium load conditions (1500 rpm/6 bar and 2000 rpm/10 bar IMEPg). The engine was equipped with two oxidation catalysts, between which was located the exhaust gas recirculation (EGR) inlet. Samples were taken at engine-out, between the catalysts, and at tailpipe locations.

Multi-hole DI injectors are being adopted in the advanced downsized DISI ICE powertrain in the automotive industry worldwide because of their robustness and cost-performance. Although their injector design and spray resembles those of DI diesel injectors, there are many basic but distinct differences due to different injection pressure and fuel properties, the sac design, lower L/D aspect ratios in the nozzle hole, closer spray-to-spray angle and hense interactions. This paper used Phase-Contrast X ray techniques to visualize the spray near a 3-hole DI gasoline research model injector exit and compared to the visible light visualization and the internal flow predictions using with multi-dimensional multi-phase CFD simulations. The results show that strong interactions of the vortex strings, cavitation, and turbulence in and near the nozzles make the multi-phase turbulent flow very complicated and dominate the near nozzle breakup mechanisms quite unlike those of diesel injections.

At the current stage of engine technology, diesel engines typically require diesel particulate filter (DPF) systems to meet recent particulate emissions standards. To assure the performance and reliability of DPF systems, profound understanding of filtration and regeneration mechanisms is required. Among extensive efforts for developing advanced DPF systems, the development of effective thermal management strategies, which control the thermal runaway taking place in oxidation of an excess amount of soot deposit in DPF, is quite challenging. This difficulty stems mainly from lack of sufficient knowledge and understanding about DPF regeneration mechanisms, which need detailed information about oxidation of diesel particulate matter (PM). Therefore, this work carried out a series of oxidation experiments of diesel particulates collected from a DPF on a diesel engine, and evaluated the oxidation rates of the samples using a thermo-gravimetric analyzer (TGA).

Detailed characteristics of morphology, nanostructures, and sizes were analyzed for particulate matter (PM) emissions from low-temperature combustion (LTC) modes of a single-cylinder, light-duty diesel engine. The LTC engines have been widely studied in an effort to achieve high combustion efficiency and low exhaust emissions. Recent reports indicate that the number of nucleation mode particles increased in a broad engine operating range, which implies a negative impact on future PM emissions regulations in terms of the nanoparticle number. However, the size measurement of solid carbon particles by commercial instruments is indeed controversial due to the contribution of volatile organics to small nanoparticles. In this work, an LTC engine was operated with various biofuel blends, such as blends (B20) of soy bean oil (soy methyl ester, SME20) and palm oil (palm methyl ester, PME20), as well as an ultra-low-sulfur diesel fuel.

In Diesel engines, fuel injection plays a critical role in performance, efficiency, and emissions. Altering parameters such as injection quantity, duration, pressure, etc. influences the injector's performance. Changes in the injection system architecture can also affect the spray behavior. Understanding of the flow near the nozzle exit can lead to the establishment of correlation to spray characteristics further downstream, and eventually its combustion behavior in the engine. Because of its high density, the near-nozzle region of the spray is difficult to study using optical techniques. This near-nozzle region of spray from high pressure injectors was studied using the quantitative and time-resolved x-ray radiography technique. This method provides high spatial and temporal resolution without significant scattering effects.

In this study, the combustion system of a light-duty compression ignition engine running on a market gasoline fuel with Research Octane Number (RON) of 91 was optimized using computational fluid dynamics (CFD) and Machine Learning (ML). This work was focused on optimizing the piston bowl geometry at two compression ratios (CR) (17 and 18:1) and this exercise was carried out at full-load conditions (20 bar indicated mean effective pressure, IMEP). First, a limited manual piston design optimization was performed for CR 17:1, where a couple of pistons were designed and tested. Thereafter, a CFD design of experiments (DoE) optimization was performed where CAESES, a commercial software tool, was used to automatically perturb key bowl design parameters and CONVERGE software was utilized to perform the CFD simulations. At each compression ratio, 128 piston bowl designs were evaluated.

A full understanding and characterization of the near-field of diesel sprays is daunting because the dense spray region inhibits most diagnostics. While x-ray diagnostics permit quantification of fuel mass along a line of sight, most laboratories necessarily use simple lighting to characterize the spray spreading angle, using it as an input for CFD modeling, for example. Questions arise as to what is meant by the “boundary” of the spray since liquid fuel concentration is not easily quantified in optical imaging. In this study we seek to establish a relationship between spray boundary obtained via optical diffused backlighting and the fuel concentration derived from tomographic reconstruction of x-ray radiography. Measurements are repeated in different facilities at the same specified operating conditions on the “Spray A” fuel injector of the Engine Combustion Network, which has a nozzle diameter of 90 μm.