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The performance of three way and NOx catalysts was evaluated on vehicles utilizing non-feedback fuel control and electronic feedback fuel control. The vehicles accumulated 80,450 km (50,000 miles) using fuels representing the extremes in hydrogen-carbon ratio available for commercial use. Feedback carburetion compared to non-feedback carburetion improved highway fuel economy by about 0.4 km/l (1 mpg) and reduced deterioration of NOx with mileage accumulation. NOx emissions were higher with the low H/C fuel in the three way catalyst system; feedback reduced the fuel effect on NOx in these cars by improving conversion efficiency with the low H/C fuel. Feedback had no measureable effect on HC and CO catalyst efficiency. Hydrocarbon emissions were lower with the low H/C fuel in all cars. Unleaded gasoline octane improver, MMT, at 0.015g Mn/l (0.06 g/gal) increased tailpipe hydrocarbon emissions by 0.05 g/km (0.08 g/mile).

A study was conducted using Ford's nine standard CFD calibration models as described in SAE paper 940323. The models are identical from the B-pillar forward but have different back end configurations. These models were created for the purpose of evaluating the effect of back end geometry variations on aerodynamic lift and drag. Detailed experimental data is available for each model in the form of surface pressure data, surface flow visualization, and wake flow field measurements in addition to aerodynamic lift and drag values. This data is extremely useful in analyzing the accuracy of the numerical simulations. The objective of this study was to determine the capability of a digital physics based commercial CFD code, PowerFLOW ® to accurately simulate the physics of the flow field around the car-like benchmark shapes.

The objective of this paper is to demonstrate that frequency domain methods for calculating structural response and fatigue damage can be more widely applicable than previously thought. This will be demonstrated by comparing results of time domain vs. frequency domain approaches for a series of fatigue/durability problems with increasing complexity. These problems involve both static and dynamic behavior. Also, both single input and multiple correlated inputs are considered. And most important of all, a variety of non-stationary loading types have been used. All of the example problems investigated are typically found in the automotive industry, with measured loads from the field or from the proving ground.

This paper presents the progress of an ongoing corrosion study of vehicle microenvironments. The study identifies the difference of corrosion microenvironments at various automotive proving grounds, using a sensor-equipped vehicle. A vehicle was instrumented for the proving ground test study. Various types of environmental sensors were installed at more than thirty-five sites on the vehicle. These sensors measured the temperature and relative humidity of the ambient air, and the temperature and time-of-wetness of the sites' surfaces. Cold rolled steel (CRS) and Zinc (Zn) corrosion rate sensors were also used in the experiments. The comparative analysis of vehicle microenvironments and corrosion rates of CRS and Zn, from three corrosion proving ground tests, will be discussed.

Two oxygenated fuels were evaluated on a single-cylinder diesel engine and compared to three hydrocarbon diesel fuels. The oxygenated fuels included canola biodiesel (canola methyl esters, CME) and CME blended with dibutyl succinate (DBS), both of which are or have the potential to be bio-derived. DBS was added to improve the cold flow properties, but also reduced the cetane number and net heating value of the resulting blend. A 60-40 blend of the two (60% vol CME and 40% vol DBS) provided desirable cold flow benefits while staying above the U.S. minimum cetane number requirement. Contrary to prior vehicle test results and numerous literature reports, single-cylinder engine testing of both CME and the 60-40 blend showed no statistically discernable change in NOx emissions relative to diesel fuel, but only when constant intake oxygen was maintained.

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.

With concerns over increasing worldwide demand for gasoline and greenhouse gases, many automotive companies are increasing their product lineup of vehicles to include flex-fuel vehicles that are capable of operating on fuel blends ranging from 100% gasoline up to a blend of 15% gasoline/85% ethanol (E85). For the purpose of this paper, data was obtained that will enable an evaluation relating to the effect the use of E85 fuel has on exhaust system surface temperatures compared to that of regular unleaded gasoline while the vehicle undergoes a typical drive cycle. Three vehicles from three different automotive manufacturers were tested. The surface of the exhaust systems was instrumented with thermocouples at specific locations to monitor temperatures from the manifold to the catalytic converter outlet. The exhaust system surface temperatures were recorded during an operation cycle that included steady vehicle speed operation; cold start and idle and wide open throttle conditions.

In this work, the effects of ozone, hydrogen, carbon monoxide, and exhaust gas recirculation (EGR) addition to Haltermann gasoline combustion were investigated. For these additives, laminar and turbulent flame speeds were experimentally determined using spherically propagating premixed flames in a constant volume combustion vessel. Two initial mixture pressures of Po = 1 and 5 bar, two initial mixture temperatures of 358 and 373 K and a range of equivalence ratios (Ф) from 0.5 to 1 were investigated. The additives were added as single, binary and ternary mixtures to Haltermann gasoline over a wide range of concentrations. For the stoichiometric mixture, the addition of 10% H2, 5% CO and 1000 ppm O3 shows remarkable enhancement (80%) in SL0compared to neat Haltermann gasoline. In addition, for this same blend, increasing the mixture initial temperature and pressure results in a significant increase in SL0compared to the neat gasoline.

A correlation of aerodynamic wind tunnels was initiated between Chrysler, Ford and General Motors under the umbrella of the United States Council for Automotive Research (USCAR). The wind tunnels used in this correlation were the open jet tunnel at Chrysler's Aero Acoustic Wind Tunnel (AAWT), the open jet tunnel at the Jacobs Drivability Test Facility (DTF) that Ford uses, and the closed jet tunnel at General Motors Aerodynamics Laboratory (GMAL). Initially, existing non-competitive aerodynamic data was compared to determine the feasibility of facility correlation. Once feasibility was established, a series of standardized tests with six vehicles were conducted at the three wind tunnels. The size and body styles of the six vehicles were selected to cover the spectrum of production vehicles produced by the three companies. All vehicles were tested at EPA loading conditions. Despite the significant differences between the three facilities, the correlation results were very good.

Self-piercing rivet (SPR) joints are a key joining technology for lightweight materials, and they have been widely used in automobile manufacturing. Manual visual crack inspection of SPR joints could be time-consuming and relies on high-level training for engineers to distinguish features subjectively. This paper presents a novel machine learning-based crack detection method for SPR joint button images. Firstly, sub-images are cropped from the button images and preprocessed into three categories (i.e., cracks, edges and smooth regions) as training samples. Then, the Artificial Neural Network (ANN) is chosen as the classification algorithm for sub-images. In the training of ANN, three pattern descriptors are proposed as feature extractors of sub-images, and compared with validation samples. Lastly, a search algorithm is developed to extend the application of the learned model from sub-images into the original button images.

Lean NOx traps are considered as a possible means to reduce diesel powertrain tail pipe NOx emissions to future stringent limits. Several publications have proposed models for lean NOx traps [1, 2, 3 and 4]. This paper focuses on a lean NOx trap model that can be used for the verification of control strategies before these strategies are implemented in target microprocessors. Strategy verification in a simulation environment is a crucial tool for reducing control strategy development and implementation time.

A fuel vapor system model (FVSMOD) has been developed to simulate vehicle evaporative emission control system behavior. The fuel system components incorporated into the model include the fuel tank and pump, filler cap, liquid supply and return lines, fuel rail, vent valves, vent line, carbon canister and purge line. The system is modeled as a vented system of liquid fuel and vapor in equilibrium, subject to a thermal environment characterized by underhood and underbody temperatures and heat transfer parameters assumed known or determined by calibration with experimental liquid temperature data. The vapor/liquid equilibrium is calculated by simple empirical equations which take into account the weathering of the fuel, while the canister is modeled as a 1-dimensional unsteady absorptive and diffusive bed. Both fuel and canister submodels have been described in previous publications. This paper presents the system equations along with validation against experimental data.

Striving for sustainable transportation solutions, hydrogen is often identified as a promising energy carrier and internal combustion engines are seen as a cost effective consumer of hydrogen to facilitate the development of a large-scale hydrogen infrastructure. Driven by efficiency and emissions targets defined by the U.S. Department of Energy, a research team at Argonne National Laboratory has worked on optimizing a spark-ignited direct injection engine for hydrogen. Using direct injection improves volumetric efficiency and provides the opportunity to properly stratify the fuel-air mixture in-cylinder. Collaborative 3D-CFD and experimental efforts have focused on optimizing the mixture stratification and have demonstrated the potential for high engine efficiency with low NOx emissions. Performance of the hydrogen engine is evaluated in this paper over a speed range from 1000 to 3000 RPM and a load range from 1.7 to 14.3 bar BMEP.

An aftertreatment system involving a LNT followed by a SCR catalyst is proposed for treating the NOx emissions from a diesel engine. NH3 (or urea) is injected between the LNT and the SCR. The SCR is used exclusively below 400°C due to its high NOx activity at low temperatures and due to its ability to store and release NH3 below 400°C, which helps to minimize NH3 and NOx slip. Above 400°C, where the NH3 storage capacity of the SCR falls to low levels, the LNT is used to store the NOx. A potassium-based LNT is utilized due to its high temperature NOx storage capability. Periodically, hydrocarbons are oxidized on the LNT under net lean conditions to promote the thermal release of the NOx. NH3 is injected simultaneously to reduce the released NOx over the SCR. The majority of the hydrocarbons are oxidized on the front portion of the LNT, resulting in the rapid release of stored NOx from that portion of the LNT.

A method of predicting brake specific fuel consumption characteristics from limited specifications of engine design has been investigated. For spark ignition engines operating on homogeneous mixtures, indicated specific fuel consumption based on gross indicated power is related to compression ratio and spark timing relative to optimum values. The influence of burn rate is approximately accounted for by the differences in spark timings required to correctly phase combustion. Data from engines of contemporary design shows that indicated specific fuel consumption can be defined as a generic function of relative spark timing, mixture air/fuel ratio and exhaust gas recirculation rate. The additional information required to generate brake specific performance maps is cylinder volumetric efficiency, rubbing friction, auxiliary loads, and exhaust back pressure characteristics.

To assess the fuel consumption of vehicles, three sets of input data are required; drive cycles, vehicle parameters, and environmental conditions. As the first part of a series of studies on real-world fuel consumption, this study focuses on the drive cycles. In principle, drive cycles should represent real-world usage. Some of them aim at a specific usage such as a city driving condition or an aggressive driving style. However, the definition of city or aggressive driving is very subjective and difficult to quantitatively correlate with the real-world usage. This study proposes a methodology to quantify the speed and dynamics of drive cycles, or vehicle speed traces in general, against the real-world usage. After reviewing parameter sets found in other studies, relative cubic speed (RCS) and positive kinetic energy (PKE) are selected to represent the speed and dynamics through energy flow balance at the wheels.

With an emerging need for gasoline particulate filters (GPFs) to lower particle emissions from gasoline direct injection (GDI) engines, studies are being conducted to optimize GPF designs in order to balance filtration efficiency, backpressure penalty, filter size, cost and other factors. Metal fiber filters could offer additional designs to the GPF portfolio, which is currently dominated by ceramic wall-flow filters. However, knowledge on their performance as GPFs is still limited. In this study, modeling on backpressure and filtration efficiency of fibrous media was carried out to determine the basic design criteria (filtration area, filter thickness and size) for different target efficiencies and backpressures at given gas flow conditions. Filter media with different fiber sizes (8 - 17 μm) and porosities (80% - 95%) were evaluated using modeling to determine the influence of fiber size and porosity.

Passive in-line catalyzed hydrocarbon (HC) traps have been used by some manufacturers in the automotive industry to reduce regulated tailpipe (TP) emissions of non-methane organic gas (NMOG) during engine cold-start conditions. However, most NMOG molecules produced during gasoline combustion are only weakly adsorbed via physisorption onto the zeolites typically used in a HC trap. As a consequence, NMOG desorption occurs at low temperatures resulting in the use of very high platinum group metal (PGM) loadings in an effort to combust NMOG before it escapes from a HC trap. In the current study, a 2.0 L direct-injection (DI) Ford Focus running on gasoline fuel was evaluated with full useful life aftertreatment where the underbody converter was either a three-way catalyst (TWC) or a HC trap. A new HC trap technology developed by Ford and Umicore demonstrated reduced TP NMOG emissions of 50% over the TWC-only system without any increase in oxides of oxygen (NOx) emissions.

Transient automotive sounds often possess a complex internal structure resulting from one or more impacts combined with mechanical and acoustic cavity resonances. This structure can be revealed by a new technique for obtaining translation-invariant scalograms from orthogonal discrete wavelet transforms. These scalograms are particularly well suited to the visualization of complex sound transients which span a wide dynamic range in time (ms to s) and frequency (∼100Hz to ∼10kHz). As examples, scalograms and spectrograms of door latch closing events from a variety of automotive platforms are discussed and compared in light of the subjective rankings of the sounds.

There is keen interest in understanding the origins of engine-out unburned hydrocarbons emitted during SI engine cold start. This is especially true for the first few firing cycles, which can contribute disproportionately to the total emissions measured over standard drive cycles such as the US Federal Test Procedure (FTP). This study reports on the development of a novel methodology for capturing and quantifying unburned hydrocarbon emissions (HC), CO, and CO2 on a cycle-by-cycle basis during an engine cold start. The method was demonstrated by applying it to a 4 cylinder 2 liter GTDI (Gasoline Turbocharged Direct Injection) engine for cold start conditions at an ambient temperature of 22°C. For this technique, the entirety of the engine exhaust gas was captured for a predetermined number of firing cycles.