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High pressure diesel sprays were visualized under vaporizing and combusting conditions in a constant-volume combustion vessel. Near-simultaneous visualization of vapor and liquid phase fuel distribution were acquired using a hybrid shadowgraph/Mie-scattering imaging setup. This imaging technique used two pulsed LED's operating in an alternative manner to provide proper light sources for both shadowgraph and Mie scattering. In addition, combustion cases under the same ambient conditions were visualized through high-speed combustion luminosity measurement. Two single-hole diesel injectors with same nozzle diameters (100μm) but different k-factors (k0 and k1.5) were tested in this study. Detailed analysis based on spray penetration rate curves, rate of injection measurements, combustion indicators and 1D model comparison have been performed.

Since transient vehicle HVAC computational fluids (CFD) simulations take too long to solve in a production environment, the goal of this project is to automatically create a lumped-parameter flow network from a steady-state CFD that solves nearly instantaneously. The data mining algorithm k-means is implemented to automatically discover flow features and form the network (a reduced order model). The lumped-parameter network is implemented in the commercial thermal solver MuSES to then run as a fully transient simulation. Using this network a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track localized temperatures near specific objects (such as equipment in vehicles).

Although soot-formation processes in diesel engines have been well characterized during the mixing-controlled burn, little is known about the distribution of soot throughout the combustion chamber after the end of appreciable heat release during the expansion and exhaust strokes. Hence, the laser-induced incandescence (LII) diagnostic was developed to visualize the distribution of soot within an optically accessible single-cylinder direct-injection diesel engine during this period. The developed LII diagnostic is semi-quantitative; i.e., if certain conditions (listed in the Appendix) are true, it accurately captures spatial and temporal trends in the in-cylinder soot field. The diagnostic features a vertically oriented and vertically propagating laser sheet that can be translated across the combustion chamber, where “vertical” refers to a direction parallel to the axis of the cylinder bore.

A wet clutch model is required in automotive propulsion system simulations for enabling robust design and control development. It commonly assumes Coulomb friction for simplicity, even though it does not represent the physics of hydrodynamic torque transfer. In practice, the Coulomb friction coefficient is treated as a tuning parameter in simulations to match vehicle data for targeted conditions. The simulations tend to deviate from actual behaviors for different drive conditions unless the friction coefficient is adjusted repeatedly. Alternatively, a complex hydrodynamic model, coupled with a surface contact model, is utilized to enhance the fidelity of system simulations for broader conditions. The theory of elastic asperity deformation is conventionally employed to model clutch surface contact. However, recent examination of friction material shows that the elastic modulus of surface fibers significantly exceeds the contact load, implying no deformation of fibers.

Exhaust manifold design is one of the more challenging tasks for the engine engineer due to the harsh thermal and severe vibration environment. Extremely high exhaust gas temperatures and dynamic loading combine to subject the manifold to high cyclic stress when the material has reduced fatigue strength due to the high temperature. A long service life before a fatigue failure is the objective in exhaust manifold design. Accumulation of fatigue damage can occur from dynamic loading and thermal loading combined. Thermal mechanical fatigue (TMF) is a primary mechanism for accumulating fatigue damage. TMF typically occurs when a vehicle driving cycle has operating conditions that repeatedly change the exhaust gas temperature between hot and cold. Another way to experience temperature cycling is through splash quenching. Splash quenching was analyzed and found to rapidly accumulate fatigue damage.

Vehicle to Vehicle Communication use case performance heavily relies on market penetration rate. The more vehicles support a use case, the better the customer experience. Enabling these use cases with acceptable quality on vehicles without built-in navigation systems, elaborate map matching and highly accurate sensors is challenging. This paper introduces a simulation framework to assess system performance in dependency of vehicle positioning accuracy for matching approach path traces in Decentralized Environmental Notification Messages (DENMs) in absence of navigation systems supporting map matching. DENMs are used for distributing information about hazards on the road network. A vehicle without navigation system and street map can only match its position trajectory with the trajectory carried in the DENM.

Morphological features of voids were characterized for T300/924 12-ply and 16-ply composite laminates at different porosity levels through the implementation of a digital microscopy (DM) image analysis technique. The composite laminates were fabricated through compression molding. Compression pressures of 0.1MPa, 0.3MPa, and 0.5MPa were selected to obtain composite plaques at different porosity levels. Tension-tension fatigue tests at load ratio R=0.1 for composite laminates at different void levels were conducted, and the dynamic stiffness degradation during the tests was monitored. Fatigue mechanisms were then discussed based on scanning electron microscope (SEM) images of the fatigue fracture surfaces. The test results showed that the presence of voids in the matrix has detrimental effects on the fatigue resistance of the material, depending on the applied load level.

The purpose of this work was to examine gasoline particle filters (GPFs) at high mileages. Soot levels for gasoline direct injection (GDI) engines are much lower than diesel engines; however, noncombustible material (ash) can cause increased backpressure, reduced power, and lower fuel economy. In this study, a post mortem was completed of two GPFs, one at 130,000 mi and the other at 150,000 mi, from two production 3.5L turbocharged GDI vehicles. The GPFs were ceramic wall-flow filters containing three-way catalytic washcoat and located downstream of conventional three-way catalysts. The oil consumption was measured to be approaching 23,000 mpqt for one vehicle and 30,000 mpqt for the other. The ash contained Ca, P, Zn, S, Fe, and catalytic washcoat. Approximately 50 wt% of the collected ash was non-lubricant derived. The filter capture efficiency of lubricant-derived ash was about 50% and the non-lubricant metal (mostly Fe) deposition rate was 0.9 to 1.2 g per 10,000 mi.

This paper focuses on finding and analyzing the relevant parameters affecting traffic flow when autonomous vehicles are introduced for ride hailing applications and autonomous shuttles are introduced for circulator applications in geo-fenced urban areas. For this purpose, different scenarios have been created in traffic simulation software that model the different levels of autonomy, traffic density, routes, and other traffic elements. Similarly, software that specializes in vehicle dynamics, physical limitations, and vehicle control has been used to closely simulate realistic autonomous vehicle behavior under such scenarios. Different simulation tools for realistic autonomous vehicle simulation and traffic simulation have been merged together in this paper, creating a realistic simulator with Hardware-in-the-Loop (HiL), Traffic-in-the-Loop (TiL), and Software in-the-Loop (SiL) simulation capabilities.

“Real world emissions” is an emerging area of focus in motor vehicle related air quality. These emissions are commonly recorded using portable emissions measurement systems (PEMS) designed for regulatory application, which are large, complex and costly. Miniature PEMS (mPEMS) is a developing technology that can significantly simplify on-board emissions measurement and potentially promote widespread use. Whereas full PEMS use analyzers to record NOx, CO, and HCs similar to those in emissions laboratories, mPEMS tend to use electrochemical sensors and compact optical detectors for their small size and low cost. The present work provides a comprehensive evaluation of this approach. It compares measurements of NOx, CO, CO2 and HC emissions from five commercial mPEMS to both laboratory and full regulatory PEMS analyzers. It further examines the use of vehicle on-board diagnostics data to calculate exhaust flow, as an alternative to on-vehicle exhaust flow measurement.

Autonomous Vehicles (AVs) operate based on image information and 3D maps generated by sensors like cameras, LIDARs and RADARs. This information is processed by the on-board processing units to provide the right actuation signals to drive the vehicle. For safe operation, these sensors should provide continuous high quality data to the processing units without interruption in all driving conditions like dust, rain, snow and any other adverse driving conditions. Any contamination on the sensor surface/lens due to rain droplets, snow, and other debris would result in adverse impact to the quality of data provided for sensor fusion and this could result in error states for autonomous driving. In particular, snow is a common contamination condition during driving that might block a sensor surface or camera lens. Predicting and preventing snow accumulation over the sensor surface of an AV is important to overcome this challenge.

Autonomous ground vehicles can use a variety of techniques to navigate the environment and deduce their motion and location from sensory inputs. Visual Odometry can provide a means for an autonomous vehicle to gain orientation and position information from camera images recording frames as the vehicle moves. This is especially useful when global positioning system (GPS) information is unavailable, or wheel encoder measurements are unreliable. Feature-based visual odometry algorithms extract corner points from image frames, thus detecting patterns of feature point movement over time. From this information, it is possible to estimate the camera, i.e., the vehicle’s motion. Visual odometry has its own set of challenges, such as detecting an insufficient number of points, poor camera setup, and fast passing objects interrupting the scene. This paper investigates the effects of various disturbances on visual odometry.

This paper describes a proton-exchange-membrane Fuel Cells (FC) system dynamic model oriented to automotive applications. The dynamic model allows analysis of FC system transient response and can be used for: a) performance assessment; b) humidification analysis; c) analysis of special modes of operation, e.g., extended idle or freeze start; d) model based FC control design and validation. The model implements a modular structure with first principle based components representation. Emphasis is placed on development of a 1-D membrane water transport model used to simulate gas to gas humidification and stack membrane water diffusion. The Simulink implementation of the model is discussed and results showing FC system transient behavior are presented.

With the rapid development of artificial intelligence, the autonomous vehicles (AV) have attracted considerable attention in the automotive industry. However, different factors negatively impact the adoption of the AVs, delaying their successful commercialization. Accretion of atmospheric icing, especially wet snow, on AV sensors causes blockage on their lenses, making them prone to lose their sight, in turn, increasing potential chances of accidents. In this study, two different designs are proposed in order to prevent snow accretion on the lenses of AVs via air flow across the lens surface. In both designs, lenses made of plain glass and superhydrophobic coated glass surfaces are tested. While some researchers have shown promise of water repellency on superhydrophobic surfaces, more snow accretion is observed on the superhydrophobic surfaces, when compared to the plain glass lenses.

As an alternative lightweight material, chopped carbon fiber reinforced Sheet Molding Compound (SMC) composites, formed by compression molding, provide a new material for automotive applications. In the present study, the monotonic and fatigue behavior of chopped carbon fiber reinforced SMC is investigated. Tensile tests were conducted on coupons with three different gauge length, and size effect was observed on the fracture strength. Since the fiber bundle is randomly distributed in the SMC plaques, a digital image correlation (DIC) system was used to obtain the local modulus distribution along the gauge section for each coupon. It was found that there is a relationship between the local modulus distribution and the final fracture location under tensile loading. The fatigue behavior under tension-tension (R=0.1) and tension-compression (R=-1) has also been evaluated.

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.

A 2-D CFD model was developed to describe the heat transfer, and reaction kinetics in a honeycomb structured ceramic diesel particulate trap. This model describes the steady state as well as the transient behavior of the flow and heat transfer during the trap regeneration processes. The trap temperature profile was determined by numerically solving the 2-D unsteady energy equation including the convective, heat conduction and viscous dissipation terms. The convective terms were based on a 2-D analytical flow field solution derived from the conservation of mass and momentum equations (Opris, 1997). The reaction kinetics were described using a discretized first order Arrhenius function. The 2-D term describing the reaction kinetics and particulate matter conservation of mass was added to the energy equation as a source term in order to represent the particulate matter oxidation. The filtration model describes the particulate matter accumulation in the trap.

The effect of friction modifiers on the low-speed frictional properties of automatic transmission fluids (ATFs) was investigated by scanning force microscopy (SFM). A clutch lining material was covered by a droplet of test ATF, and a steel tip was scanned over the sample. The scanning speeds were varied from 0.13 to 8.56 mm /sec, and the frictional force was deduced from the torsion of the SFM cantilever. A reduction in dynamic friction due to the addition of the friction modifier was clearly observed over the entire speed range. This indicates that the boundary lubrication mechanism is dominant under this condition, and therefore surface-active friction modifiers can effectively improve the frictional characteristics. The friction reduction was more pronounced at lower sliding speeds. Thus addition of friction modifiers produced a more positive slope in the μ-ν (friction vs. sliding speed) plots, and would contribute to make wet clutch systems less susceptible to shudder vibrations.

Stress analyses of complex automotive components can be nearly impossible to achieve due to extreme difficulties in generating a realistic finite element model. A digital image based finite element approach was used to generate a 3-D finite element model from computed tomography (CT) scans of two automotive transmission cases. For the first case, original CT slices of 1024x1024x208 provided by ARACOR Inc. (Sunnyvale, CA) were used to generate a 3-D finite element model containing nearly 400,000 8-node brick elements. For the second case, 770x870x759 CT slices were used to generate a 3-D finite element model containing approximately 650,000 3-D elements. The mesh data generation from CT data for both cases took 6 minutes each on an engineering workstation. The resulting finite element meshes were analyzed using a specially designed finite element equation solver.

This paper describes the results of permeation and sorption tests conducted to assess the properties of several plastic materials as barriers to fuel. The materials examined include ethylene-vinyl alcohol copolymers (EVOH), nylon, high density polyethylene, polyketone, poly-vinyledene fluoride (PVDF) as well as tetra-fluoro-ethylene, hexa-fluoro-propylene and vinyledene fluoride terpolymers (THV). The permeation from thin films of these materials exposed to methanol or CM15 was analyzed (speciated) by gas chromatography. These results are compared to those of parallel sorption experiments conducted on the same materials. The goal of this work is to determine the materials best suited for fuel barrier applications.