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For this work, a methodology of modeling and predicting fuel consumption in a hybrid vehicle as a function of the engine operating temperature has been developed for cold ambient operation (-7°C, 266°K). This methodology requires two steps: 1) development of a temperature dependent engine brake specific fuel consumption (BSFC) map, and, 2) a data-fitting technique for predicting engine temperature to be used as an input to the temperature dependent BSFC maps. For the first step, response surface methodology (RSM) techniques were applied to generate brake specific fuel consumption (BSFC) maps as a function of the engine thermal state. For the second step, data fitting techniques were also used to fit a simplified lumped capacitance heat transfer model using several experimental datasets. Utilizing these techniques, an analysis of fuel consumption as a function of thermal state across a broad range of engine operating conditions is presented.

Optical soot pyrometry is a mature experimental technique that has been applied to a broad range of combustion systems for measuring soot temperature and concentration. Even though the method is widely used and well documented, the line of sight nature of the technique makes the interpretation of its results challenging. Notably, gradients in temperature and soot concentration along the line of sight or across the field of view can introduce significant levels of uncertainty in the results. This paper presents a numerical study where the signal from the experimental two-color pyrometry technique in a marine diesel engine reference experiment is reconstructed employing computational fluid dynamics (CFD) and a detailed Line-by-Line (LBL) spectral radiation model. The analysis is aimed at qualitatively supporting interpretability of experimental observations.

Highly time resolved measurements of cylinder pressure acquired simultaneously from three transducers were used to investigate the nature of knocking combustion and to identify biases that the pressure measurements induce. It was shown by investigating the magnitude squared coherence (MSC) between the transducer signals that frequency content above approximately 40 kHz does not originate from a common source, i.e., it originates from noise sources. The major source of noise at higher frequency is the natural frequency of the transducer that is excited by the impulsive knock event; even if the natural frequency is above the sampling frequency it can affect the measurements by aliasing. The MSC analysis suggests that 40 kHz is the appropriate cutoff frequency for low-pass filtering the pressure signal. Knowing this, one can isolate the knock event from noise more accurately.

This paper reports investigations on diesel jet transients, accounting for internal nozzle flow and needle motion. The calculations are performed with Large Eddy Simulation (LES) turbulence model by coupling the internal and external multiphase flows simultaneously. Short and multiple injection strategies are commonly used in internal combustion engines. Their features are significantly different from those generally found in steady state conditions, which have been extensively studied in the past, however, these conditions are seldom reached in modern engines. Recent researches have shown that residual gas can be ingested in the injector sac after the end-of-injection (EOI) and undesired dribbles can be produced. Moreover, a new injection event behaves differently at the start-of-injection (SOI) depending on the sac initial condition, and the initial spray development can be affected for the first few tens of μs.

This paper presents the results of efficiency, emissions, and performance testing of a supercharged, hydrogen-powered, four-cylinder engine. Tests were run at various speeds, loads, and air/fuel ratios in order to identify advantageous operating regimes. The tests revealed that a maximum thermal brake efficiency of 37% could be achieved and that certain operating regimes could achieve NOx emissions as low as 1 ppm without aftertreatment. Measurement of cylinder pressure traces in all four cylinders allowed a detailed assessment of cylinder-cylinder deviation. Several measures to further increase hydrogen engine performance in order to reach the goals set by the U.S. Department of Energy are being discussed.

Two modern light-duty passenger vehicles were selected for chassis dynamometer testing to evaluate differences in performance end efficiency resulting from CNG and gasoline combustion in a vehicle-based context. The vehicles were chosen to be as similar as possible apart from fuel type, sharing similar test weights and identical driveline configurations. Both vehicles were tested over several chassis dynamometer driving cycles, where it was found that the CNG vehicle exhibited 3-9% lower fuel economy than the gasoline-fueled subject. Performance tests were also conducted, where the CNG vehicle's lower tractive effort capability and longer acceleration times were consistent with the lower rated torque and power of its engine as compared to the gasoline model. The vehicles were also tested using quasi-steady-state chassis dynamometer techniques, wherein a series of engine operating points were studied.

This paper reports an effort to measure particulate emissions from a modern light duty CIDI engine equipped with a common-rail fuel injection system, a closed loop EGR system and a state-of-the-art aftertreatment system. Particulate emissions both upstream and downstream of the catalyst were measured using an SMPS system and a TEOM while operating the engine at various steady-state conditions. The measurements upstream of the catalyst show that the particulate emissions are strongly dependent on the engine speed, load and EGR conditions. The measurements downstream of the catalyst show the effectiveness of the catalyst in reducing particulate mass emissions by 20-80%, with reductions in particulate mean diameters averaging about 10%. The trends observed are discussed in terms of previously established particulate formation and destruction mechanisms.

Many concepts of premixed diesel combustion at reduced temperatures have been investigated over the last decade as a means to simultaneously decrease engine-out particle and oxide of nitrogen (NO ) emissions. To overcome the trade-off between simultaneously low particle and NO emissions versus high "diesel-like" combustion efficiency, a new dual-fuel technique called Reactivity Controlled Compression Ignition (RCCI) has been researched. In the present study, particle size distributions were measured from RCCI for four gasoline:diesel compositions from 65%:35% to 84%:16%, respectively. Previously, fuel blending (reactivity control) had been carried out by a port fuel injection of the higher volatility fuel and a direct in-cylinder injection of the lower volatility fuel. With a recent mechanical upgrade, it was possible to perform injections of both fuels directly into the combustion chamber.

The limited spatial area in conventional diesel particulate filter (DPF) systems requires frequent regenerations to remove collected particulate matter (PM) emissions, consequently resulting in higher energy consumption and potential material failure. Due to the complex geometry and difficulty in access to the internal structure of diesel particulate filters, in addition, many important characteristics in filtration processes remain unknown. In this work, therefore, the geometry of DPF membrane channels was modified basically to increase the filtration areas, and their filtration characteristics were evaluated in terms of pressure drop across the DPF membranes, effects of soot loading on pressure drop, and qualitative soot mass distribution in the membrane channels. In this evaluation, an analytical model was developed for pressure drop, which allowed a parametric study with those modified membranes.

As emerging automated vehicle technology is making advances in safety and reliability, engineers are also exploring improvements in energy efficiency with this new paradigm. Powertrain efficiency receives due attention, but also impactful is finding ways to reduce driving losses in coordinated-driving scenarios. Efforts focused on simulation to quantify road load improvements require a sufficient amount of background validation work to support them. This study uses a practical approach to directly quantify road load changes by testing the coordinated driving of two vehicles on a test track at various speeds (64, 88, 113 km/h) and vehicle time gaps (0.3 to 1.3 s). Axle torque sensors were used to directly measure the load required to maintain steady-state speeds while following a lead vehicle at various gap distances.

On-road fuel economy is known to vary significantly between individual trips in real-world driving conditions. This work introduces a methodology for rapidly simulating a specific vehicle’s fuel economy over the wide range of real-world conditions experienced across the country. On-road test data collected using a highly instrumented vehicle is used to refine and validate this modeling approach. Model accuracy relative to on-road data collection is relevant to the estimation of “off-cycle credits” that compensate for real-world fuel economy benefits that are not observed during certification testing on a chassis dynamometer.

A fully instrumented Tesla Model 3 was used to collect thousands of hours of real-world automated driving data, encompassing both Autopilot and Full Self-Driving modes. This comprehensive dataset included vehicle operational parameters from the data busses, capturing details such as powertrain performance, energy consumption, and the control of advanced driver assistance systems (ADAS). Additionally, interactions with the surrounding traffic were recorded using a perception kit developed in-house equipped with LIDAR and a 360-degree camera system. We collected the data as part of a larger program to assess energy-efficient driving behavior of production connected and automated vehicles. One important aspect of characterizing the test vehicle is predicting its car-following behavior. Using both uncontrolled on-road tests and dedicated tests with a lead car performing set speed maneuvers, we tuned conventional adaptive cruise control (ACC) equations to fit the vehicle’s behavior.

This paper performs a parametric analysis of the influence of numerical grid resolution and turbulence model on jet penetration and mixture formation in a DI-H2 ICE. The cylinder geometry is typical of passenger-car sized spark-ignited engines, with a centrally located single-hole injector nozzle. The simulation includes the intake and exhaust port geometry, in order to account for the actual flow field within the cylinder when injection of hydrogen starts. A reduced geometry is then used to focus on the mixture formation process. The numerically predicted hydrogen mole-fraction fields are compared to experimental data from quantitative laser-based imaging in a corresponding optically accessible engine. In general, the results show that with proper mesh and turbulence settings, remarkable agreement between numerical and experimental data in terms of fuel jet evolution and mixture formation can be achieved.

It is beneficial but challenging to operate spark-ignition engines under highly lean and dilute conditions. The unstable ignition behavior can result in downgraded combustion performance in engine cylinders. Numerical approach is serving as a promising tool to identify the ignition requirements by providing insight into the complex physical/chemical phenomena. An effort to simulate the early stage of flame kernel initiation in lean and dilute fuel/air mixture has been made and discussed in this paper. The simulations are set to validate against laboratory results of spark ignition behavior in a constant volume combustion vessel. In order to present a practical as well as comprehensive ignition model, the simulations are performed by taking into consideration the discharge circuit analysis, the detailed reaction mechanism, and local heat transfer between the flame kernel and spark plug.

In this work, a turbulent combustion model is developed for large eddy simulation (LES) using a novel flamelet tabulation technique based on the framework of the multi-flamelet representative interactive flamelet (RIF) model. The overall aim is to develop a detailed model with elaborate chemistry mechanisms, LES turbulence models and highly resolved grids leveraging the computational cost advantage of a tabulated model. A novel technique of implementing unsteady flamelet libraries by using the residence time instead of the progress variables is proposed. In this study, LES of n-dodecane spray flame is performed using the tabulated turbulent combustion model along with a dynamic structure subgrid model. A high-resolution mesh is employed with a cell size of 62.5 microns in the entire spray and combustion regions. This model is then validated against igniting n-dodecane sprays under diesel engine conditions.

While sulfur in diesel fuels helps reduce friction and prevents wear and galling in fuel pump and injector systems, it also creates environmental pollution in the form of hazardous particulates and SO2 emissions. The environmental concern is the driving force behind industry's efforts to come up with new alternative approaches to this problem. One such approach is to replace sulfur in diesel fuels with other chemicals that would maintain the antifriction and antiwear properties provided by sulfur in diesel fuels while at the same time reducing particulate emissions. A second alternative might be to surface-treat fuel injection parts (i.e., nitriding, carburizing, or coating the surfaces) to reduce or eliminate failures associated with the use of low-sulfur diesel fuels. Our research explores the potential usefulness of a near-frictionless carbon (NFC) film developed at Argonne National Laboratory in alleviating the aforementioned problems.

Applying nanotechnology to thermal engineering, ANL has addressed the interesting and timely topic of nanofluids. We have developed methods for producing both oxide and metal nanofluids, studied their thermal conductivity, and obtained promising results: (1) Stable suspensions of nanoparticles can be achieved. (2) Nanofluids have significantly higher thermal conductivities than their base liquids. (3) Measured thermal conductivities of nanofluids are much greater than predicted. For these reasons, nanofluids show promise for improving the design and performance of vehicle thermal management systems. However, critical barriers to further development and application of nanofluid technology are agglomeration of nanoparticles and oxidation of metallic nanoparticles. Therefore, methods to prevent particle agglomeration and degradation are required.

A computational, three-dimensional approach to investigate the behavior of diesel soot particles in the micro-channels of wall-flow Diesel Particulate Filters is presented. The KIVA3V CFD code, already extended to solve the 2D conservation equations for porous media materials [1], has been enhanced to solve in 2-D and 3-D the governing equations for reacting and compressible flows through porous media in non axes-symmetric geometries. With respect to previous work [1], a different mathematical approach has been followed in the implementation of the numerical solver for porous media, in order to achieve a faster convergency as source terms were added to the governing equations. The Darcy pressure drop has been included in the Navier-Stokes equations and the energy equation has been extended to account for the thermal exchange between the gas flow and the porous wall.

This experimental work focuses on defining the detailed morphology of secondary emission products derived from the combustion of cerium (Ce) fuel-borne catalyst (FBC) doped with diesel fuel. Cerium is often used to promote the oxidation of diesel particulates collected in diesel aftertreatment systems, such as diesel particulate filters (DPFs). However, it is suspected that the secondary products could be emitted from the vehicle tailpipe without being effectively filtered by the aftertreatment systems. In this work, these secondary emissions were identified by means of a high-resolution transmission electron microscope (TEM), and their properties were examined in terms of morphology and chemistry. In preparation for fuel doping, a cerium-based aliphatic organic compound solution was mixed with a low-sulfur (110 ppm) diesel fuel at 50 ppm in terms of weight concentration.

A multidimensional simulation of Auxiliary Gas Injection (AGI) for late cycle oxygen enrichment was exercised to assess the merits of AGI for reducing the emissions of soot from heavy duty diesel engines while not adversely affecting the NOx emissions of the engine. Here, AGI is the controlled enhancement of mixing within the diesel engine combustion chamber by high speed jets of air or another gas. The engine simulated was a Caterpillar 3401 engine. For a particular operating condition of this engine, the simulated soot emissions of the engine were reduced by 80% while not significantly affecting the engine-out NOx emissions compared to the engine operating without AGI. The effects of AGI duration, timing, and orientation are studied to confirm the window of opportunity for realizing lower engine-out soot while not increasing engine out NOx through controlled enhancement of in-cylinder mixing.