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Corrosion affects all industrial sectors where metals or metal alloys are used in their structures. In the automotive industry, the continuous search for lightweight parts has increased the demand for effective corrosion protection, in order to improve vehicle performance without compromising durability and safety. In this scenario, coatings are essential elements to preserve and protect vehicle parts from various environmental aggressions. Automotive coatings can be classified into primers, topcoats, clearcoats, and specialty coatings. Primers provide corrosion resistance and promote adhesion between the substrate and topcoat. Topcoats provide color, gloss, and durability to the coating system, while clearcoats enhance the appearance and durability of the finish. Specialty coatings provide additional properties, such as scratch resistance, chemical resistance, and UV protection.

A DMS (Driver Monitoring System) is one of the most important safety features that assist in the monitoring functions and alert drivers when distraction or drowsiness is detected. The system is based in a DSMC (Driver Status Monitoring Camera) mounted in the vehicle's dash, which has a predefined set of operational requirements that must be fulfilled to guarantee the correct operation of the system. These conditions represent a trade space analysis challenge for each vehicle since both the DSMC and the underlying vehicle’s requirements must be satisfied. Relying upon the camera’s manufacturer evaluation for every iteration of the vehicle’s design has proven to be time-consuming, resources-intensive, and ineffective from the decision-making standpoint.

Fretting fatigue was observed in standard cylindrical fatigue samples at the regions in contact with the grips of the test frames during fatigue testing for AlSi10Mg aluminum alloy produced by laser powder bed fusion process (L-PBF). The failure of the fatigue sample grips occurs much earlier than the failure of the gauge section. This results in a damaged sample and the sample cannot be reused to continue the test. This type of failure is rarely seen in materials produced by traditional manufacturing processes. In this study, X-ray residual stress analysis was performed to understand the cause of failure for L-PBF AlSi10Mg with the as-built surface condition. The result indicates that the fretting fatigue failure was caused by the strong tensile residual stress in the as-built state combining with the fretting wear between the sample and the grip. A few potential solutions to avoid the fretting fatigue failure were investigated.

Currently the automotive industry has been under extremely important technological changes. Part of these changes are related to the way that users interact with the vehicle and fundamental components are the new digital cluster and screens. These devices have created a disruption in the way information is transmitted to the user, being essential for vehicle operation, including safety. Due to new operating conditions, multiple evaluations need to be performed, one of them is the solar temperature Load to ensure correct operation without compromising user safety. This test is required to identify the thermal performance on the screens mounted on the instrument panel. The performance identification is performed on both sides, analytical and physical. In regards finite element simulation it represents the solar chamber as the main source of heat and being the main mechanism of transmission the radiation.

Laser welding of the magnesium-bearing AA5xxx aluminum alloys is often beset by keyhole instability, especially in the lap through joint configuration. This phenomenon is characterized by periodic collapse of the keyhole leaving large voids in the weld zone. In addition, the top surface can exhibit undercut and roughness. In full penetration welds, keyhole instability can also produce a spikey root and severe top surface concavity. These discontinuities could prevent a weld from achieving engineering specification compliance, pose a craftsmanship concern, or reduce the strength and fatigue performance of the weld. In the case of a full penetration weld, a spikey root could compromise part fit-up and corrosion protection, or damage adjacent sheet metal, wiring, interior components, or trim.

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.

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.

Vehicle fire investigators often use the existence of burn patterns, along with the amount and location of fire damage, to determine the fire origin and its cause. The purpose of this paper is to study the effects of ventilation location on the interior burn patterns and burn damage of passenger compartment fires. Four similar Ford Fusion vehicles were burned. The fire origin and first material ignited were the same for all four vehicles. In each test, a different door window was down for the duration of the burn test. Each vehicle was allowed to burn until the windshield, back glass, or another window, other than the window used for ventilation, failed, thus changing the ventilation pattern. At that point, the fire was extinguished. Temperatures were measured at various locations in the passenger compartment. Video recordings and still photography were collected at all phases of the study.

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.

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.

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.

Stress and strain measurement of high density polyethylene (HDPE) fuel tanks under dynamic loading is challenging. Motion tracking combined with computer vision was employed to evaluate the strain in an HDPE fuel tank being dynamically loaded with a crash pulse. Traditional testing methods such as strain gages are limited to the small strain elastic region and HDPE testing may exceed the range of the strain gage. In addition, strain gages are limited to a localized area and are not able to measure the deformation and strain across a discontinuity such as a pinch seam. Other methods such as shape tape may not have the response time needed for a dynamic event. Motion tracking data analysis was performed by tracking the motion of specified points on a fuel tank during a dynamic test. An HDPE fuel tank was mounted to a vehicle section and a sled test was performed using a Seattle sled to simulate a high deltaV crash. Multiple target markers were placed on the fuel tank.

The long-term weathering behavior of three different 3D printable, non-stabilized, UV cure resin formulations (A and B with thiol-ene base, and C with acrylate chemistry) was studied using tensile testing, nano-indentation, and photoacoustic infrared (FTIR-PAS) spectroscopy. To this end, type I tensile bars were printed from each resin system using a 3D printer, and were post UV-cured under a broad spectrum source. Systems A and C showed a similar trend after weathering. They first experienced an increase in modulus and tensile strength, due to additional crosslinking of the residual unreacted species. This increase in mechanical properties was followed by a drop in modulus, tensile strength, and percent elongation, due to the over-crosslinking and consequent embrittlement. System B, however, showed remarkable retention of the mechanical properties before/after weathering.

In the recent years, adjoint optimization has gained popularity in the automotive industry with its growing applications. Since its inclusion in the mainstream commercial CFD solvers and its continuously added capabilities over the years, its productive usage became readily available to many engineers who were previously limited to interfacing the customized adjoint source code with CFD solvers. The purpose of this work is to demonstrate using an adjoint solver a method to optimize duct shape that meets multiple design objectives simultaneously. To overcome one of the biggest challenges in the duct design, i.e. the severe packaging constraints, the method here uses geometrically constrained adjoint to ensure that the optimum shape always fits into the user-defined packaging space. In this work, adjoint solver and surface sensitivity calculations are used to develop the optimization method.

Capacitance sensing is the technology that detects the presence of nearby objects by measuring the change in capacitance. A change in capacitance is triggered either by a change in dielectric constant, area of overlap or distance of separation between the electrodes of the capacitor. It is a technology that finds wide use in applications such as touch screens, proximity sensing etc. Drawing motivation from such applications, this paper investigates how capacitive sensing can be employed to detect the presence and posture of occupants inside vehicles. Compared to existing solutions, the proposed approach is low-cost, easy to deploy and highly efficient. The sensing system consists of a capacitance-sensing mat that is embedded with copper foils and an associated sensing circuitry. Inside the mat the foils are arranged in rows and columns to form several touch-nodes across the surface of the mat.

This paper summarizes the development of a wireless message from infrastructure-to-vehicle (I2V) for safety applications based on Dedicated Short-Range Communications (DSRC) under a cooperative agreement between the Crash Avoidance Metrics Partners LLC (CAMP) and the Federal Highway Administration (FHWA). During the development of the Curve Speed Warning (CSW) and Reduced Speed Zone Warning with Lane Closure (RSZW/LC) safety applications [1], the Basic Information Message (BIM) was developed to wirelessly transmit infrastructure-centric information. The Traveler Information Message (TIM) structure, as described in the SAE J2735, provides a mechanism for the infrastructure to issue and display in-vehicle signage of various types of advisory and road sign information. This approach, though effective in communicating traffic advisories, is limited by the type of information that can be broadcast from infrastructures.

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.

SiC devices have inherent fast switching capabilities due to their superior material properties, and are considered potential candidates to replace Si devices for traction inverters in electrified vehicles in future. However, due to the comparatively low gate threshold voltage, SiC devices may encounter oscillatory false triggering especially during fast switching. This paper analyzed the causes of false triggering, and also studied the impact of a critical parasitic parameter - common source inductance. It is shown that crosstalk is the main cause for the false triggering in the case and some positive common source inductance help to mitigate the crosstalk issue. A packaging layout method is proposed to create the positive common source inductance through layout of control terminals / busbars, and/or the use of control terminal bonded wires at different height.

Tumble motion plays a significant role in modern spark-ignition engines in that it promotes mixing of air/fuel for homogeneous combustion and increases the flame propagation speed for higher thermal efficiency and lower combustion variability. Cycle-by-cycle variations in the flow near the spark plug introduce variability to the initial flame kernel development, stretching, and convection, and this variability is carried over to the entire combustion process. The design of current direct-injection spark-ignition engines aims to have a tumble flow in the vicinity of the spark plug at the time of ignition. This work investigates how the flow condition changes in the vicinity of the spark plug throughout the late compression stroke via high-speed imaging of a long ignition discharge arc channel and its stretching, and via flow field measurement by particle imaging velocimetry.