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Magnesium and aluminum alloys offer lightweighting opportunities in automotive applications. Joining of dissimilar materials, however, generally requires methods that do not involve fusion. This paper explores the use of self-pierce riveting (SPR) to join magnesium to aluminum alloys for structural and closure applications. The preliminary results indicate that SPR is a viable option for joining aluminum extrusions to magnesium die castings, as well as stamped sheet aluminum to quick-plastic-formed (QPF) sheet magnesium.

As mass reduction becomes an increasingly important enabler for fuel economy improvement, having a robust structural development process that can comprehend Vehicle Dynamics-specific requirements is correspondingly important. There is a correlation between the stiffness of the body structure and the performance of the vehicle when evaluated for ride and handling. However, an unconstrained approach to body stiffening will result in an overly-massive body structure. In this paper, the authors employ loads generated from simulation of quasi-static and dynamic vehicle events in ADAMS, and exercise structural finite element models to recover displacements and deflected shapes. In doing so, a quantitative basis for considering structural vehicle dynamics requirements can be established early in the design/development process.

Experimental decklids for the Cadillac STS sedan were made with Al AA5083 sheet outer panels and Mg AZ31B sheet inner panels using regular-production forming processes and hardware. Joining and coating processes were developed to accommodate the unique properties of Mg. Assembled decklids were evaluated for dimensional accuracy, slam durability, and impact response. The assemblies performed very well in these tests. Explicit and implicit finite element simulations of decklids were conducted, and showed that the Al/Mg decklids have good stiffness and strength characteristics. These results suggest the feasibility of using Mg sheet closure panels from a structural perspective.

Cast aluminum alloys are increasingly used in cyclically loaded automotive structural applications for light weight and fuel economy. The fatigue resistance of aluminum castings strongly depends upon the presence of casting flaws and characteristics of microstructural constituents. The existence of casting flaws significantly reduces fatigue crack initiation life. In the absence of casting flaws, however, crack initiation occurs at the fatigue-sensitive microstructural constituents. Cracking and debonding of large silicon (Si) and Fe-rich intermetallic particles and crystallographic shearing from persistent slip bands in the aluminum matrix play an important role in crack initiation. This paper presents fatigue life models for aluminum castings free of casting flaws, which complement the fatigue life models for aluminum castings containing casting flaws published in [1].

There is an increasing demand in automated manufacturability analysis of metal castings at the initial stages of their design. This paper presents a system developed for virtual manufacturability analysis of casting components. The system can be used by a casting designer to evaluate manufacturability of a part designed for various manufacture processes including casting, heat treatment, and machining. The system uses computational geometrics and geometric reasoning to extract manufacturing features and geometry characteristics from a part CAD model. It uses an expert system and a design database consisting of metal casting, heat treatment and machining process knowledge and rules to present manufacturability analysis results and advice to the designer. Application of the system is demonstrated for the manufacturability assessment of automotive cast aluminum components.

During sheet metal forming, the friction and surface roughness change as the sheet slides, bends and stretches against the tools. This study assessed evolution of friction and surface roughness changes on aluminum sheet with two surface finish conditions, mill finish (MF) and electron discharge texture (EDT), in both the longitudinal and the transverse rolling directions of the sheet. The sheets were tested using a three pin Draw Bead Simulator (DBS). Surface roughness of the sheet evolved as a result of bending at the first shoulder, reverse bending at the middle pin, bending at the second shoulder and unbending at the exit. Stretching conditions and sheet-pin contact were also varied to see the impact on surface roughness. In general, the largest surface roughness change for the transverse direction was observed at the convex side of the exit shoulder pin and on the convex side of the first shoulder for the longitudinal direction.

Aluminum sheet is commercially available in three surface finishes, mill finish (MF), electric discharge texture (EDT), and dull finish (DF). This surface finish impacts the friction behavior during sheet metal forming. A study was done to compare ten commercially available sheet samples from several suppliers. The friction behavior was characterized in the longitudinal and transverse directions using a Draw Bead Simulator (DBS) test, resulting in a coefficient of friction (COF) value for each material. Characterization of the friction behavior in each direction provides useful data for formability analysis. To quantitatively characterize the surface finish, three-dimensional MicroTexture measurements were done with a WYKO NT8000 instrument. In general, the MF samples have the smoothest surface, with Sa values of 0.20-0.30 μm and the lowest COF values. The EDT samples have the roughest surface, with Sa values of 0.60-1.00 μm, and the highest COF values.

The preform annealing process is a two-stage stamping method for shaping non age-hardenable (i.e. 5000 series) aluminum sheet panels in which the panel is heat treated in between the two steps to improve overall formability of the material. The intermediate annealing heat treatment eliminates the cold work accumulated in the material during the first draw. The process enables the ability to form more complex parts than a conventional aluminum stamping process. A demonstration of local annealing for this process was conducted to form a one-piece aluminum liftgate inner panel for a large sport utility vehicle using the steel product geometry without design concessions. In prior work, this process was demonstrated by placing the entire panel in a convection oven for several minutes to completely anneal the cold work.

Cast aluminum alloys are normally quenched after solution treatment or solidification process to improve aging responses. Rapid quenching can lead to high residual stress and severe distortion which significantly affects dimension stability, functionality and particularly performance of the product. To simulate residual stress and distortion induced during quenching, a finite element based approach was developed by coupling an iterative zone-based transient heat transfer algorithm with material thermo-viscoplastic constitutive model. With the integrated models, the numeric predictions of residual stresses and distortion in the quenched aluminum castings are in a good agreement with experimental measurements.

It is important to understand the accuracy level of the formability analysis for any new process so that correct predictions can be made in product and die design. This report focuses on the formability analysis methodology developed for the preform anneal process. In this process, the aluminum panel is partially formed, annealed to eliminate the cold work from the first step, and then formed to the final shape using the same die. This process has the ability to form more complex parts than conventional aluminum stamping, and has been demonstrated on a complex one-piece door inner and a complex one-piece liftgate inner with AA5182-O3. Both panels only required slight design modifications to the original steel product geometry. This report focuses on the formability analysis correlation with physical panels for the liftgate inner, considering both full panel anneal in a convection oven and local annealing of critical areas.

Incomplete vehicles are partially manufactured by an Original Equipment Manufacturer (OEM) and subsequently sold to and completed by a final-stage manufacturer. Section S8.8, Final-Stage Manufacturers and Alterers, of Federal Motor Vehicle Safety Standard (FMVSS) 126 states “Vehicle that are manufactured in two or more stages or that are altered (within the meaning of 49 CFR 567.7) after having been previously certified in accordance with Part 567 of this chapter, are not subject to the requirements of S8.1 through S8.5. Instead, all vehicles produced by these manufacturers on or after September 1, 2012, must comply with this standard.” The FMVSS 126 compliance of the completed vehicle can be certified in three ways: by the OEM provided no alterations are made to identified components (TYPE 1), conditionally by the OEM provided the final-stage manufacturer follows specific guidelines (TYPE 2), or by the final-stage manufacturer (TYPE 3).

Recent advancements in simulation software and computational hardware make it realizable to simulate a full vehicle system comprised of multiple sub-models developed in different modeling languages. The so-called, co-simulation allows one to develop a control strategy and evaluate various aspects of a vehicle system, such as fuel efficiency and vehicle drivability, in a cost-effective manner. In order to study the feasibility of the synchronized parallel processing in co-simulation this paper presents two co-simulation frameworks for a complete vehicle system with multiple heterogeneous subsystem models. In the first approach, subsystem models are co-simulated in a serial configuration, and the same sub-models are co-simulated in a parallel configuration in the second approach.

This paper discusses observability of the vehicle states using different sensor configurations as well as fault-tolerant estimation of these states. The optimality of the sensor configurations is assessed through different observability measures and by using a 3-DOF linear vehicle model that incorporates yaw, roll and lateral motions of the vehicle. The most optimal sensor configuration is adopted and an observer is designed to estimate the states of the vehicle handling dynamics. Robustness of the observer against sensor failure is investigated. A fault-tolerant adaptive estimation algorithm is developed to mitigate any possible faults arising from the sensor failures. Effectiveness of the proposed fault-tolerant estimation scheme is demonstrated through numerical analysis and CarSim simulation.

This study concerns the generation of response surfaces for kinematics and injury prediction in pedestrian impact simulations using human body model. A 1000-case DOE (Design of Experiments) study with a Latin Hypercube sampling scheme is conducted using a finite element pedestrian human body model and a simplified parametric vehicle front-end model. The Kriging method is taken as the approach to construct global approximations to system behavior based on results calculated at various points in the design space. Using the response surface models, human lower limb kinematics and injuries, including impact posture, lateral bending angle, ligament elongation and bone fractures, can be quickly assessed when either the structural dimensions or the structural behavior of the vehicle front-end design change. This will aid in vehicle front-end design to enhance protection of pedestrian lower limbs.

This paper presents the implementation of an off-line optimized torque vectoring controller on an electric-drive vehicle with four in-wheel motors for driver assistance and handling performance enhancement. The controller takes vehicle longitudinal, lateral, and yaw acceleration signals as feedback using the concept of state-derivative feedback control. The objective of the controller is to optimally control the vehicle motion according to the driver commands. Reference signals are first calculated using a driver command interpreter to accurately interpret what the driver intends for the vehicle motion. The controller then adjusts the braking/throttle outputs based on discrepancy between the vehicle response and the interpreter command.

To investigate the effect of aeration on fluid-elastomer compatibility, 4 types of elastomers were aged in three gear lubes. The four types of elastomers include a production fluorinated rubber (FKM) and production hydrogenated nitrile rubber (HNBR) mixed by the part fabricator, a standard low temperature flexible fluorinated rubber (FKM, ES-4) and a standard ethylene-acrylic copolymer (AEM, ES-7) mixed by SAE J2643 approved rubber mixer. The three gear lubes are Fluid a, Fluid b and Fluid c, where Fluid b is a modified Fluid with additional friction modifier, and Fluid c is friction modified chemistry from a different additive supplier. The aeration effect tests were performed at 125°C for 504 hours. The aerated fluid aging test was performed by introducing air into fluid aging tubes as described in General Motors Company Materials Specification GMW16445, Appendix B, side-by-side with a standard ASTM D471 test.

In this paper, a finite element methodology is given in which finite element models of a three-weld Al-Cu plate is created with support and loading conditions emulating those seen in an optical lab. Harmonic response is sought for the models under the presumption that various defective welds are present. The numerical results are carefully examined to determine the guideline frequency range so the actual optical experiment can be carried out more efficiently.

In today's light-weight vehicles, the strength of spot welds plays an important role in overall product integrity, reliability and customer satisfaction. Naturally, there is a need for a quick and reliable technique to inspect the quality of the welds. In the past, the primary quality control tests for detecting weld defects are the destructive chisel test and peel test [1]. The non-destructive evaluation (NDE) method currently used in industry is based on ultrasonic inspection [2, 3, 4]. The technique is not always successful in evaluating the nugget size, nor is it effective in detecting the so-called “cold” or “stick” welds. Therefore, it is necessary to develop a precise and reliable noncontact NDE method for spot welds. There have been numerous studies in predicting the weld nugget size by considering the spot-weld process [5, 6].

Delivering the appropriate material data for CAE analysis of plastic components is not as straight forward as it would seem to be. While a few of the properties typically used by resin manufacturers and material engineers to describe a plastic are useful to the analysis community (density, CLTE), most are not (flexural modulus, notched izod). In addition some properties such as yield stress are defined differently by the analysis community than by the materials community. Lastly, secondary operations such as painting or chrome plating significantly change the behavior of components with plastic substrates. The materials engineering community and the CAE analysis community must work together closely to develop the material data necessary to increase the capability of the analysis. This paper will examine case studies where these issues have required modifications to the material property data to increase the fidelity of the CAE analysis.

Key fobs, also known as remote keys or remote transmitters, have become a common piece of equipment in today's vehicle, being ubiquitous in every market segment. Once limited to remote locking and unlocking operations, today's key fobs can be used to control many comfort and security features beyond locking and unlocking, such as alarm system operation, vehicle locate, approach lighting, memory seat recall, and remote starting systems. Key fobs are designed to be easy to use as well as easy to carry and transport in personal containers, such as purses, pockets, wallets, and the like. Accordingly, as with other personal effects, key fobs and other portable remote devices can be lost or misplaced or can be otherwise difficult to find. Even with careful tracking of a remote device, children and pets, among other factors, can make location difficult. Moreover, multiple remote devices are often distributed with each vehicle.