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The front camera module is a fundamental component of a modern vehicle’s active safety architecture. The module supports many active safety features. Perception of the road environment, requests for driver notification or alert, and requests for vehicle actuation are among the camera software’s key functions. This paper presents a novel method of testing these functions virtually. First, the front camera module software is compiled and packaged in a Docker container capable of running on a standard Linux computer as a software in the loop (SiL). This container is then integrated with the active safety simulation tool that represents the vehicle plant model and allows modeling of test scenarios. Then the following simulation components form a closed loop: First, the active safety simulation tool generates a video data stream (VDS). Using an internet protocol, the tool sends the VDS to the camera SiL and other vehicle channels.

Disc brakes operate with very close proximity of the brake pads and the brake rotor, with as little as a tenth of a millimeter of movement of the pads required to bring them into full contact with the rotor to generate braking torque. It is usual for a disc brake to operate with some amount of residual drag in the fully released state, signifying constant contact between the pads and the rotor. With this contact, every miniscule movement of the rotor pushes against the brake pads and changes the forces between them. Sustained loads on the brake corner, and maneuvers such as cornering, can both produce rotor movement relative to the caliper, which can push it steadily against one or both of the brake pads. This can greatly increase the residual force in the caliper, and increase drag. This dependence of drag behavior on the movement of the brake rotor creates some vehicle-dependent behavior.

A student team from Brigham Young University (BYU) set a new record for the world's fastest electric drag racecar. The team modified a production EV1 donated to the university by the General Motors Corporation and installed a bank of 160 UltraCapacitors rated at 2700 farads each. This paper describes the design of the capacitor pack, the car's drive train, the charging method and other modifications of the vehicle. Here we also discuss performance and race data from an official quarter-mile drag race sanctioned by the National Electric Drag Racing Association. A simulation model for vehicle performance was also developed and is presented here.

In the context of vehicle electrification, improving vehicle aerodynamics is not only critical for efficiency and range, but also for driving experience. In order to balance the necessary trade-offs between drag and downforce without significant impact on the vehicle styling, we see an increasing amount of active aerodynamic solutions on high-end passenger vehicles. Active rear spoilers are one of the most common active aerodynamic features. They deploy at high vehicle speed when additional downforce is required [1, 2]. For a vehicle with an active rear spoiler, the aerodynamic performance is typically predicted through simulations or physical testing at different static spoiler positions. These positions range from fully stowed to fully deployed. However, this approach does not provide any information regarding the transient effects during the deployment of the rear spoiler, which can be critical to understanding key performance aspects of the system.

NASA's plans to implement the Vision for Space Exploration include extensive human-robot cooperation across an enterprise spanning multiple missions, systems, and decades. To make this practical, strong enterprise-level interface standards (data, power, communication, interaction, autonomy, and physical) will be required early in the systems and technology development cycle. Such standards should affect both the engineer and operator roles that humans adopt in their interactions with robots. For the engineer role, standards will result in reduced development lead-times, lower cost, and greater efficiency in deploying such systems. For the operator role, standards will result in common autonomy and interaction modes that reduce operator training, minimize workload, and apply to many different robotic platforms. Reduced quantities of spare hardware could also be a benefit of standardization.

Edge stretchability reduction induced by mechanical trimming is a critical issue in advanced high strength steel applications. In this study, the tooling effects on the trimmed edge damage were evaluated by the specially designed in-plane hole expansion test with the consideration of three punch geometries (flat, conical, and rooftop), three cutting clearances (6%, 14%, and 20%) and two materials grades (DP980 and DP1180). Two distinct fracture initiation modes were identified with different testing configurations, and the occurrence of each fracture mode depends on the tooling configurations and materials grades. Digital Image Correlations (DIC) measurements indicate the materials are subject to different deformation modes and the various stress conditions, which result in different fracture initiation locations.

Electric motor whine is one of the main noise sources of hybrid and electric vehicles. Motor air gap eccentricity due to propulsion system deflection, part tolerances and manufacturing variation is typically ignored in motor NVH design and analysis. Such eccentricity can be a dominant noise source by amplifying critical motor whine orders up to 10 dB, leading to poor NVH robustness. However, this problem cannot be explained by conventional method based on symmetric 2D approach. New 3D electromagnetic (EM) and NVH analyses are developed and validated to accurately predict air gap induced motor noise to enhance NVH robustness: First, a true 3D full 360-degree electric motor model is developed to model asymmetric air gap distribution along motor stack length. Predicted 3D EM forces are mapped to mechanical finite-element mesh over the cylindrical stator surface.

Semi-Permanent Mold (SPM) cast aluminum alloy cylinder heads are commonly used in gasoline and diesel internal combustion engines. The cast aluminum cylinder heads must withstand severe cyclic mechanical and thermal loads throughout their lifetime. The casting process is inherently prone to introducing casting defects and microstructural heterogeneity. Porosity, which is one of the most dominant volumetric defects in such castings, has a significant detrimental effect on the fatigue life of these components since it acts as a crack initiation site. A reliable analytical model for Thermo-Mechanical Fatigue (TMF) life prediction must take into account the presence of these defects. In previous publications, it has been shown that the mechanism-based TMF damage model (DTMF) is able to predict with good accuracy crack locations and the number of cycles to propagate an initial defect into a critical crack size in aluminum cylinder heads considering ageing effects.

Cast austenitic stainless steels, such as 1.4837Nb, are widely used for turbo housing and exhaust manifolds which are subjected to elevated temperatures. Due to assembly constraints, geometry limitation, and particularly high temperatures, thermomechanical fatigue (TMF) issue is commonly seen in the service of those components. Therefore, it is critical to understand the TMF behavior of the cast steels. In the present study, a series of fatigue tests including isothermal low cycle fatigue tests at elevated temperatures up to 1100°C, in-phase and out-of-phase TMF tests in the temperature ranges 100-800°C and 100-1000°C have been conducted. Both creep and oxidation are active in these conditions, and their contributions to the damage of the steel are discussed.

The automotive industry is continuously striving to reduce vehicle mass by reducing the mass of components including wheel bearings. A typical wheel bearing assembly is mostly steel, including both the wheel and knuckle mounting flanges. Mass optimization of the wheel hub has traditionally been accomplished by reducing the cross-sectional thickness of these components. Recently bearing suppliers have also investigated the use of alternative materials. While bearing component performance is verified through analysis and testing by the supplier, additional effects from system integration and performance over time also need to be comprehended. In a recent new vehicle architecture, the wheel bearing hub flange was reduced to optimize it for low mass. In addition, holes were added for further mass reduction. The design met all the supplier and OEM component level specifications.

Commercially available Generation 3 (GEN3) advanced high strength steels (AHSS) have inherent capability of replacing press hardened steels (PHS) using cold stamping processes. 980 GEN3 AHSS is a cold stampable steel with 980 MPa minimum tensile strength that exhibits an excellent combination of formability and strength. Hot forming of PHS requires elevated temperatures (> 800°C) to enable complex deep sections. 980 GEN3 AHSS presents similar formability as 590 DP material, allowing engineers to design complex geometries similar to PHS material; however, its cold formability provides implied potential process cost savings in automotive applications. The increase in post-forming yield strength of GEN3 AHSS due to work and bake hardening contributes strongly toward crash performance in energy absorption and intrusion resistance.

Adiabatic heating during plastic straining can slow the diffusionless shear transformation of austenite to martensite in steels that exhibit transformation induced plasticity (TRIP). However, the extent to which the transformation is affected over a strain rate range of relevance to automotive stamping and vehicle impact events is unclear for most third-generation advanced high strength TRIP steels. In this study, an 1180MPa minimum tensile strength TRIP steel with carbide-free bainite is evaluated by measuring the variation of retained austenite volume fraction (RAVF) in fractured tensile specimens with position and strain. This requires a combination of servo-hydraulic load frame instrumented with high speed stereo digital image correlation for measurement of strains and ex-situ synchrotron x-ray diffraction for determination of RAVF in fractured tensile specimens.

Third generation advanced high strength steels (AHSS) that rely on the transformation of austenite to martensite have gained growing interest for implementation into vehicle architectures. Previous studies have identified a dependency of the rate of austenite decomposition on the amount of strain and the associated strain path imposed on the sheet. The rate and amount of austenite transformation can impact the work hardening behavior and tensile properties. However, a deeper understanding of the impact on toughness, and thus crash performance, is not fully developed. In this study, the strain path and strain amounts were systematically controlled to understand the associated correlation to impact toughness in the end application condition (strained and baked). Impact toughness was evaluated using an instrumented Charpy machine with a single sheet v-notch sample configuration.

Third generation advanced high strength steels (3GAHSS) are increasingly used in automotive for light weighting and safety body structure components. However, high material strength usually introduces higher springback that affects the dimensional accuracy. The ability to accurately predict springback in simulations is very important to reduce time and cost in stamping tool and process design. In this work, tension and compression tests were performed and the results were implemented to generate Isotropic/Kinematic hardening (I/KH) material models on a 3GAHSS steel with 980 MPa minimum tensile strength. Systematic material model parametric studies and evaluations have been conducted. Case studies from full-scale industrial parts are provided and the predicted springback results are compared to the measured springback data. Key variables affecting the springback prediction accuracy are identified.

The high performance brake systems of today are usually in a delicate balance - walking the fine line between being overpowered by some of the most potent powertrains, some of the grippiest tires, and some of the most demanding race tracks that the automotive world has ever seen - and saddling the vehicle with excess kilograms of unsprung mass with oversized brakes, forcing significant compromises in drivability with oversized tires and wheels. Brake system design for high performance vehicles has often relied on a very deep understanding of friction material performance (friction, wear, and compressibility) in race track conditions, with sufficient knowledge to enable this razor’s edge design.

Prior to making rotational vibration measurements with a laser vibrometer, it is good practice to establish that the instrument is operating properly. This can be accomplished by comparative measurement of a rotational vibration source with known amplitude and frequency. This paper describes the design and development of a rotational vibration apparatus with known amplitude and frequency to be used as a reference for comparison to concurrent and co-located measurements made by a rotational laser vibrometer (RLV). The comparative measurements acquired with the apparatus are helpful to verify proper laser vibrometer operation in between regular calibration intervals, and/or whenever the functionality of the vibrometer is suspect. In the subject apparatus, a Cardan shaft with variable input speed and angle is used to provide output torsional vibration with variable frequency and amplitude.

Retained austenite stability to both mechanically induced transformation and athermal transformation is of great importance to the fabrication and in-vehicle performance of automotive advanced high strength steels. Selected cold-rolled advanced high strength steels containing retained austenite with minimum tensile strengths of 980 MPa and 1180 MPa were pre-strained to pre-determined levels under uniaxial tension in the rolling direction and subsequently cooled to temperatures as low as 77 K. Room temperature uniaxial tensile results of pre-strained and cooled steels indicate that retained austenite is stable to athermal transformation to martensite at all tested temperatures and pre-strain levels. To evaluate the combined effects of temperature and pre-strain on impact behavior, stacked Charpy impact testing was conducted on the same 980 MPa minimum tensile strength steel following similar pre-straining in uniaxial tension.

A major barrier, preventing RFSSW from use by manufacturers, is the long cycle time that has been historically associated with making a weld. In order for RFSSW to become a readily implementable welding solution, cycle times must be reduced to an acceptable level, similar to that of well developed, competing spot joining processes. In the present work, an investigation of the RFSSW process is conducted to evaluate factors that have traditionally prevented the process from achieving fast cycle times. Within this investigation, the relationship between cycle time and joint quality is explored, as is the meaning and measurement of cycle time in the RFSSW process. Claims and general sentiment found in prior literature are challenged regarding the potential for high-speed RFSSW joints to be made.

This report presents the results of a CFD study to develop a bodywork package to improve the aerodynamic performance of the Brigham Young University (BYU) Electric Streamliner. A comparison of the pressure distribution and the flow around the baseline and final ‘recommended’ configuration is also presented. The effect of the CFD developed body geometry to the vehicle has been to increase downforce by almost 300lbf when it is at 200mph, while reducing drag by 8.5lbf. The final lift to drag ratio is -1.56 as compared to the .67 baseline.

A Machine Learning (ML) approach is presented to correlate in-cylinder images of early flame kernel development within a spark-ignited (SI) gasoline engine to early-, mid-, and late-stage flame propagation. The objective of this study was to train machine learning models to analyze the relevance of flame surface features on subsequent burn rates. Ultimately, an approach of this nature can be generalized to flame images from a variety of sources. The prediction of combustion phasing was formulated as a regression problem to train predictive models to supplement observations of early flame kernel growth. High-speed images were captured from an optically accessible SI engine for 357 cycles under pre-mixed operation. A subset of these images was used to train three models: a linear regression model, a deep Convolutional Neural Network (CNN) based on the InceptionV3 architecture and a CNN built with assisted learning on the VGG19 architecture.