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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.

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).

To cope with the increasing number of advanced features (e.g., smart-phone integration and side-blind zone alert.) being deployed in vehicles, automotive manufacturers are designing flexible hardware architectures which can accommodate increasing feature content with as fewer as possible hardware changes so as to keep future costs down. In this paper, we propose a formal and quantitative definition of flexibility, a related methodology and a tool flow aimed at maximizing the flexibility of an automotive hardware architecture with respect to the features that are of greater importance to the designer. We define flexibility as the ability of an architecture to accommodate future changes in features with no changes in hardware (no addition/replacement of processors, buses, or memories). We utilize an optimization framework based on mixed integer linear programming (MILP) which computes the flexibility of the architecture while guaranteeing performance and safety requirements.

The first set of SAE J2643 Standard Reference Elastomers (SRE) was developed in 2004. It was composed of a group of 10 compounds covering multiple elastomer families. Since then, more advanced materials from many elastomer families have been introduced to the automotive industry. The purpose of this study is to add a few more reference compounds to SAE J2643, to enhance the portfolio on FKM, AEM and ACM to reflect advancements in elastomer technology, and make it suitable for a variety of fluids, such as transmission fluid and engine oil. Fourteen standard elastomer compounds were involved in this study, covering various materials currently used in automotive powertrain static and dynamic sealing applications. Participants include OEMs, major rubber manufacturers, a fluid additive company and an independent lab. Manufacturers of each test compound provided formulations, designated ingredients from defined sources, and detailed mixing and molding procedures.

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.

As an innovative electric vehicle with some new approaches to energy usage and vehicle performance balance, the Chevy Volt required a special relationship between the OEM and tire supplier community. This paper details this relationship and how advanced tools and technology were leveraged between OEM and supplier to achieve tire component and overall vehicle performance results.

Headliner material plays an important role in occupant protection in situations involving head impact into the interior vehicle roof area. Accurate characterization of its mechanical properties is therefore extremely important for prediction of its behavior during interior impact assessment of a vehicle. Headliner material typically consists of two main layers: the substrate layer which provides structural integrity and impact protection, and the fabric-foam layer which provides proper interior fit and appearance. Both layers vary significantly in thickness and composition between different manufacturers. This paper investigates effects of the layer thickness on compressive strength and deformation of several different headliner materials.

Industry standards and practices define a number of mathematical and physical methods to estimate the cargo carrying volume capacity of a vehicle. While some have roots dating back decades, others try to assess the utility of the space for cargo by subjective measurements. Each these methods have their own inherent merits and deficiencies. The purpose of this paper is to highlight the differences in calculated cargo volume amongst the following practices: Society of Automobile Engineers (SAE) J1100[1] International Organization for Standardization (ISO 3832)[2], Global Car manufacturer's Information Exchange group (GCIE)[3], Consumer Reports[4]. This paper provides a method and associated rationale for constructing a new cargo volume calculation practice that attempts to harmonize these procedures into a more contiguous practice. This homologation will benefit publishing industry, vehicle manufacturers and customers alike.

Given the fast changing market demands, the growing complexity of features, the shorter time to market, and the design/development constraints, the need for efficient and effective verification and validation methods are becoming critical for vehicle manufacturers and suppliers. One such example is fault-tree analysis. While fault-tree analysis is an important hazard analysis/verification activity, the current process of translating design details (e.g., system level and software level) is manual. Current experience indicates that fault tree analysis involves both creative deductive thinking and more mechanical steps, which typically involve instantiating gates and events in fault trees following fixed patterns. Specifically for software fault tree analysis, a number of the development steps typically involve instantiating fixed patterns of gates and events based upon the structure of the code. In this work, we investigate a methodology to translate software programs to fault trees.

Aeration properties of lubricants is an increasing concern as the design of powertrain components, specifically transmissions, continue to become more compact leading to smaller sumps and higher pressure requirements. Although good design practices are the most important factors in mitigating the aeration level of the fluid, the fluid properties themselves are also a contributing factor. This paper investigates the aeration properties of specific base oils commonly used to formulate modern transmission fluids using the General Motors Company Aeration Bench Test found in GMN10060. The test matrix includes thirteen different fluids representing a cross-section of base oil types, manufacturers, and viscosity grades. Per the procedure found in GMN10060, the bench test measures the aeration time, de-aeration time, and percent maximum aeration of the fluid at three temperatures, 60°C, 90°C, and 120°C. In the end, the results are compared with four commercially available transmission fluids.

1 As global automotive manufacturers prepare for the introduction of HFO-1234yf as the low Global Warming Potential (GWP) refrigerant solution in Europe and North America concerns over compressor durability due to oil migration still remain. This preliminary study evaluates several different variables that affect oil migration. Several compressor suppliers each having their own unique oil formulation for HFO-1234yf were included. Comparisons between vehicle tests and various accelerated lab test methods are made. In R134a automotive system the thresholds that cause compressor warranty are well understood. This study will compare AC systems running with HFO-1234yf at the same time identical systems with R134a are run to understand the relative effect of HFO-1234yf versus R134a.

The design of an existing GM exhaust system is analyzed for possible design modifications that may result in lower shipping costs between the supplier facility that manufactures the exhaust system and the assembly plant that installs the system. Investment, changes in piece cost, and other factors are examined in order to determine design changes based upon a rate of return on the investment.

GM has recently developed two kinds of vehicle electrification architectures. First is VOLTec, a heavy electrification architecture, and second is eAssist, a light electrification architecture. An overview, of IGBT power modules & inverters used in VOLTec and eAssist, is presented. Alternative power modules from few cooperative suppliers are also described in a benchmarking study using key metrics. Inverter test set up, procedure and instrumentation used in GM Power Electronics Development Lab, Milford are described. GM electrification journey depends on Power Electronics lab' passive test benches; double pulse tester, inductive resistive load bench and active emulator test cell without electric machines. Such test benches are preferred before dyne test cells are used for inverter software/hardware integration and motor durability tests cycles. Specific test results are presented.

ASIL decomposition is a method described in the ISO 26262 standard for the assignment of ASILs to redundant requirements. Although ASIL decomposition appears to have similar intent to the hardware fault tolerance concept of IEC 61508-2, ASIL decomposition is not intended to reduce ASIL assignments to hardware elements for random hardware failures, but instead focuses on functions and requirements in the context of systematic failures. Based on our participation in the development of the standard, the method has been applied in different ways in practice, not all of which are fully consistent with the intent of the standard. Two potential reasons that may result in the use of “modified” ASIL algebra include the need of OEMs to partition a system and specify subsystem requirements to suppliers and the need for designers to construct systems bottom up.

Rubber isolators and bushings are very important components for vehicle performance. However, one often finds it is difficult to get the dynamic properties to be readily used in CAE analysis, either from suppliers or from OEM's own test labs. In this paper, the author provides an analytical method to obtain the dynamic stiffness of an exhaust isolator, using ABAQUS and iSight, with tested or targeted isolator static stiffness information. The analysis contains two steps. The first step is to select the (rubber/EPDM) material properties for the FE isolator model by matching the static stiffness with either the targeted spring rate (linear or nonlinear) or the (tested) load / deflection curve. The second step is to perform dynamic analysis on the statically “validated” FE isolator model to obtain its dynamic properties.