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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).

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.

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.

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.

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.

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.

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.

Hardware benchmarking of body overall stiffness and joint stiffness of the best-in-class competitive vehicles is a common practice in the automobile industry. However, this process does not provide design insights of competitive body structures, which relate stiffness performance to key architectural designs. To overcome this drawback, a CAD body-in-prime model of a competitive vehicle is developed using laser/optical scanning technology and a corresponding CAE model is built based on the CAD data. A deep-dive structural efficiency study is conducted using this model and “pros” and “cons” of the architectural design of each individual joint and each section of major load-carrying members of this body structure are identified. This analytical benchmarking (or reverse engineering) process enables a company to adopt best-in-class design practices and achieve competitive advantages in vehicle designs.

With the increasing demand for safety, energy saving and emission reduction, Advanced High Strength Steels (AHSS) have become very attractive materials for automobile makers. Welding of AHSS remains one of the technical challenges in the successful application of AHSS in automobile structures, especially when durability of the welded structures is required. In this study, 2.0 mm uncoated DP780 was investigated. GMAW welding parameters for lap joints of this steel were developed in order to obtain different weld geometries defined by weld toe angle, weld leg sizes, and weld penetration. Metallurgical properties of the joints were evaluated using optical microscopy and scanning electron microscopy (SEM). Static and fatigue tests were conducted on the welded joints. Effect of weld geometry and HAZ softening on fatigue performance including fatigue life, crack initiation site and propagation path of the joints will be analyzed.

Optical based sensor systems for vehicle based detection and warning systems are under development to reduce accidents and limit injuries caused by accidents. (1, 2, 3) In order to validate these types of detection systems, it is necessary to perform real world tests. In the case of pedestrian detection systems, this is very difficult in the field for safety reasons. Instead, simulated tests are more desirable. This paper describes work to understand the effectiveness of using virtual pedestrians as surrogates for real world pedestrian detection.

A methodology is developed that incorporates high resolution CFD flowfield information and a particle trajectory simulation, aimed at addressing Paint Transfer Efficiency (PTE) for bell sprayers. Given a solid model for the bell sprayer, the CFD simulation, through automeshing, determines a high resolution Cartesian volume mesh (14-20 million cells). With specified values of the initial shaping air, transient and steady-state flow field information is obtained. A particle trajectory visualization tool called SpraySIM uses this complicated flowfield information to determine the particle trajectories of the paint particles under the influence of drag, gravity and electrostatic potential. The sensitivity of PTE on shaping air velocity, charge-to-mass ratio, potential, and particle diameter are examined.

This study compared laser and fine plasma technology for cutting typical electro-galvanized steel and aluminum automotive stampings. Comparisons were made of various aspects of cut quality, accuracy, disturbance of parent material, cycle time, and capital and operating costs. A sensitivity analysis was included to determine how different scenarios would impact the operating costs. It was found that both processes were capable of high quality cuts at 3800mm/min. Capital savings were achievable through the fine plasma system, but careful consideration of the specific application was essential. This work will allow for an advised comparison of options for sheet metal flexible cutting.

The automotive industry is in constant pursuit of alternative materials and processes to address the ever changing needs of their customer and the environment. This paper presents findings from a study using a laser hybrid process (laser with MIG) to join aluminum-silicon coated boron steel (USIBOR). In this report the influence of heat from the laser hybrid welding process and its effect on the coated boron steel is discussed. In order to understand the affect from laser hybrid joining process, bead on plate experiments were conducted using 1.0 mm, 1.6 mm and 2.0 mm thick coupons. Further, two lap joint configurations were also investigated using the 1.6 mm and 2.0 mm thick coupons. Based on the test results, a significant reduction in tensile strength was observed at the Heat Affected Zone (HAZ).

Typical automotive joints are lap, coach, butt and miter joints. In tubular joining applications, a coach joint is common when one tube is joined to another tube without the use of brackets. Various fusion joining processes are popular in joining coach joints. Common fusion joining processes are Gas Metal Arc Welding (GMAW), Laser and Laser Hybrid, and Gas Tungsten arc welding (GTAW). In this study, fusion welded 2.0 mm uncoated DP780 steel coach joints were investigated. Laser, Gas metal arc welding (GMAW), and laser hybrid (Laser + GMAW) welding processes were selected. Metallurgical properties of the DP780 fusion welds were evaluated using optical microscopy. Static and fatigue tests were conducted on these joints for all three joining processes. It was found that joint fit-up, type of welding process, and process parameters, especially travel speed, have significant impact on static and fatigue performance of the coach joints in this study.

Wavelets are a powerful mathematical tool used to multi-resolution time-frequency decomposition of signals, in order to analyze them in different scales and obtain different aspects of the information. Despite being a relatively new tool, wavelets have being applied in several areas of human knowledge, especially in signal processing, with emphasis in encoding and compression of image, video and audio. Based on a previous successful applications (FRAZIER, 1999) together a commitment to quality results, this paper evaluates the use of the Discrete Wavelet Transform (DWT) as an compression algorithm to reduce the amount of data collected in road load signals (load history) which are used by the durability engineering teams in the automotive industry.