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A hydrogen economy is an increasingly popular solution to lower global carbon dioxide emissions. Previous research has been focused on the economic conditions necessary for hydrogen to be cost competitive, which tends to neglect the effectiveness of greenhouse gas mitigation for the very solutions proposed. The holistic carbon footprint assessment of hydrogen production, distribution, and utilization methods, otherwise known as “well-to-wheels” carbon intensity, is critical to ensure the new hydrogen strategies proposed are effective in reducing global carbon emissions. When looking at these total carbon intensities, however, there is no single clear consensus regarding the pathway forward. When comparing the two fundamental technologies of steam methane reforming and electrolysis, there are different scenarios where either technology has a “greener” outcome.

A correlation of aerodynamic wind tunnels was initiated between Chrysler, Ford and General Motors under the umbrella of the United States Council for Automotive Research (USCAR). The wind tunnels used in this correlation were the open jet tunnel at Chrysler's Aero Acoustic Wind Tunnel (AAWT), the open jet tunnel at the Jacobs Drivability Test Facility (DTF) that Ford uses, and the closed jet tunnel at General Motors Aerodynamics Laboratory (GMAL). Initially, existing non-competitive aerodynamic data was compared to determine the feasibility of facility correlation. Once feasibility was established, a series of standardized tests with six vehicles were conducted at the three wind tunnels. The size and body styles of the six vehicles were selected to cover the spectrum of production vehicles produced by the three companies. All vehicles were tested at EPA loading conditions. Despite the significant differences between the three facilities, the correlation results were very good.

The need for accurate virtual prototyping prediction is well documented in the literature. For welded body structures one notable shortcoming has been the ability for finite element analysis (FEA) to accurately predict the failure of welded joints due to cyclic loading. A new approach to representing spot-welds for durability evaluation in automotive sheet metal structures is presented here. Excellent correlation with spot-weld failures in actual tests have been observed through this modeling approach. We present a method of representing spot-welds using the finite element method. This method has shown to be able of predicting the behavior of spot-welds prior to the build of any prototypes or testing. Further, for spot-weld failures we present evidence that reveals which radial quadrant of the spot-weld will contain the failure. This method also allows engineers to determine the mechanism of failure. This paper describes in detail the spot-weld modeling method.

As automotive OEMs (Original Equipment Manufacturer) struggle to reach a balance between Design and Performance, environmental legislations continues to demand more rapid gains in vehicle efficiency. As a result, more attention is being given to the contributions of both tire and wheels. Not only tire rolling resistance, but also tire and wheel aerodynamics are being shown to be contributors to overall efficiency. To date, many studies have been done to correlate CFD simulations of rotating wheels both in open and closed wheeled environments to windtunnel results. Whereas this ensures proper predictive capabilities, little focus has been given to thoroughly explaining the physics that govern this complex environment. This study seeks to exhaustively investigate the complex interactions between the ground, body, and a rotating tire/wheel.

Fast-running metamodels (surrogates or response surfaces) that approximate multivariate input/output relationships of time-consuming CAE simulations facilitate effective design trade-offs and optimizations in the vehicle development process. While the cross-validated nonparametric metamodeling methods are capable of capturing the highly nonlinear input/output relationships, it is crucial to ensure the adequacy of the metamodel error estimates. Moreover, in order to circumvent the so-called curse-of-dimensionality in constructing any nonlinear multivariate metamodels from a realistic number of expensive simulations, it is necessary to reliably eliminate insignificant inputs and consequently reduce the metamodel prediction error by focusing on major contributors. This paper presents a robust data-adaptive nonparametric metamodeling procedure that combines a convergent variable screening process with a robust 2-level error assessment strategy to achieve better metamodel accuracy.

Deionized (DI) water is being used for humidification and cooling on some fuel cell designs. This highly purified water is corrosive, yet the high purity is required to maintain the function and durability of the fuel cell. A study of the deionized water system was undertaken to determine the effect of various materials on water quality, and also to determine the effect of deionized water on each material. The test setup was designed to circulate fluid from a reservoir, similar to an actual application. The fluid temperature, pressure, and flow rate were controlled. The resistivity of the water was observed and recorded. Pre- and post-testing of the water and the materials was performed. The goal is to achieve system cleanliness and durability similar to a stainless steel system using lighter, less expensive materials. This paper describes the test setup, test procedures, and the overall results for the eight materials tested.

The present work aims to characterize the microstructure of valvetrain camshaft lobes that are currently applied in the automotive industry, obtained by different processing routes. The cam lobe microstructure has been assessed by microscopy, whereas the mechanical properties by hardness profile measurements on the surface region. Microconstituents type and form, composing the final microstructure at the cam lobe work region, are defined by the casting route and/or post-heat treatment process other than alloy chemical composition, so that knowledge and control of processing route is vital to assure suitable valvetrain system assembly performance and durability. Most of the mechanical solicitations on the part occur at the interface between cam and follower; the actual contact area is significantly smaller than the apparent area. As a result, the microstructure at and near the surface performs a direct role on the performance of the valvetrain, cam lobe and its counterpart.

Reductions of hardware costs as well as implementations of new innovative functions are the main drivers of today's automotive electronics. Indeed more and more resources are spent on adapting existing solutions to different environments. At the same time, due to the increasing number of networked components, a level of complexity has been reached which is difficult to handle using traditional development processes. The automotive industry addresses this problem through a paradigm shift from a hardware-, component-driven to a requirement- and function-driven development process, and a stringent standardization of infrastructure elements. One central standardization initiative is the AUTomotive Open System ARchitecture (AUTOSAR). AUTOSAR was founded in 2003 by major OEMs and Tier1 suppliers and now includes a large number of automotive, electronics, semiconductor, hard- and software companies.

In the North American automotive market, cylinder deactivation by means of engine valve deactivation is becoming a significant enabler in reducing the Brake Specific Fuel Consumption (BSFC) of large displacement engines. This allows for the continued market competitiveness of large displacement spark ignition (SI) engines that provide exceptional performance with reduced fuel consumption. As an alternative to a major engine redesign, the Active Fuel Management™ (AFM™) system is a lower cost and effective technology that provides improved fuel economy during part-load conditions. Cylinder deactivation is made possible by utilizing innovative new base engine hardware in conjunction with an advanced control system. In the GM 3.9L V-6 Over Head Valve (OHV) engine, the standard hydraulic roller lifters on the engine's right bank are replaced with deactivating hydraulic roller lifters and a manifold assembly of oil control solenoids.

This paper presents an overview of the aerodynamic development of the 2019 Chevrolet Corvette C7 ZR1. Extensive wind tunnel testing and computational fluid dynamics simulations were completed to engineer the ZR1’s aerodynamics to improve lift-to-drag efficiency and track capability over previous Corvette offerings. The ZR1 architecture changes posed many aerodynamic challenges including increased vehicle cooling, strict packaging demands, wider front track width, and aggressive exterior styling. Through motorsports-inspired aerodynamic development, the ZR1 was engineered to overcome these challenges through the creation of new devices such as a raised rear wing and front underwing. The resulting Standard ZR1 achieved a top speed of 212 mph making it the fastest Corvette ever [1]. Optionally, the ZR1 with the ZTK Performance Package provides the highest downforce of any Corvette, generating approximately 950 pounds at the ZTK’s top speed [1].

Hyper-elastic seals are extensively used in automotive applications for sealing various joints in assembly. They are also used in sealing battery packs. They are used in various sizes and shapes. Most of the gaskets used are solid gaskets. Hollow gaskets are also being used. Hollow gaskets typically have a fluid like air trapped inside. Analyzing these hollow gaskets also requires involving the physics of the fluid inside. The trapped fluid affects the performance of the gasket like contact pressure and width. Objective of this study is to analyze the hollow gasket performance including the effect of air trapped inside. The effect of air on performance of the hollow seal is also studied. Fluid Cavity capability in ABAQUS was selected after literature study to simulate the effect of trapped fluid (Air) on seal performance.

Internal combustion engines (ICEs) exhaust emissions, particularly nitrogen oxides (NOx), have become a growing environmental and health concern. The biggest challenge for contemporary ICE industry is the development of clean ICEs, and the use of advanced design tools like Computational Fluid Dynamics (CFD) simulation is paramount to achieve this goal. In particular, the development of aftertreatment systems like Selective Catalyst Reduction (SCR) is a key step to reduce NOx emissions, and accurate and efficient CFD models are essential for its design and optimization. In this work, we propose a novel 3D-CFD methodology, which uses a Machine Learning (ML) approach as a surrogate model for the SCR catalyst chemistry, which aims to enhance accuracy of the simulations with a moderate computational cost. The ML approach is trained on a dataset generated from a set of 1D-CFD simulations of a single channel of an SCR catalyst.

Currently, the dominant technology used in the manufacture of mass-market automobile structures is sheet-metal stamping because of its suitability for producing accurate, strong, durable components in large quantities [1]. While cost-effective and fast for high-volume applications, the cost of manufacturing stamping dies is difficult to profitably amortize over a low-volume product in any but the most high-priced vehicle segments. This study examines the application of automated fabrication technologies as an alternative to stamping for the production of low-volume body structure components, including the impacts on both design and performance.

Economic market forces and increasing environmental awareness of gasoline have led to interest in developing alternatives to gasoline, and extending the current global supply for transportation fuels. One viable strategy is the use of alternative alcohol fuels for combustion engines, with ethanol and methanol in various concentration ranges proposed and in-use. Utilizing and citing data from this review, a comprehensive overview of the materials selection and engineering challenges facing metals, plastics and elastomers are presented. The engineering approach and solution-sets discussed will focus on production feasibility and implementation. The effects from the fuel chemistry and quality of fuel ethanol produced on the related vehicle components are discussed.

Manual transmissions for passenger cars are facing pressures due to rapid growth of automatic transmissions, which already represents more than 60% of Brazil market, and from higher torque demand due to strict emission legislation, which turbo engines had presented great contribution to it. To solve this contradictory issue, gears with higher strength and lower cost have been studied to replacement Nickel by Niobium in the steels. Furthermore, this technology could be applied to solve the issues with electrified vehicle, where high torque, speed and lifetime are demanded pursued for gears. This study aimed to build prototypes and compare the S-N curves, fracture analysis, microstructure for three kinds of steels (QS4321 with Ni, QS1916 FG without Ni & with Nb and QS 1916 without Ni and Nb) in the condition carburized, hardened and tempered with and without shot peening.

The GM Aerodynamics Laboratory (GMAL) was modified in 2001 to reduce the background noise level and provide a semi-anechoic test section for wind noise testing. The walls and ceiling of the test section were lined with acoustic foam and foam-filled turning vanes were installed in the corners. Portions of the wind tunnel circuit were also treated with fiberglass material covered by perforated sheet metal panels. High skin drag due to roughness of the foam surfaces, along with high blockage due to the large turning vanes, increased the wind tunnel circuit losses so that the maximum wind speed in the test section was reduced. The present study calculates the averaged total pressure losses at three locations to evaluate the reductions in skin drag and blockage from proposed modifications to the circuit, which were intended to increase the test section wind speed without compromising noise levels.

The evolution toward the use of electrostatic painting processes has been driven primarily by environmental legislation and efforts to improve efficiencies in the painting process. The development of conductive substrate material compliments the industry trend toward a green environment through further reductions in emissions of volatile organic compounds during the painting process. Traditionally, electrostatic painting of thermoplastics requires that a conductive primer be applied to the substrate prior to topcoat application. The conductive polymer blend of polyphenylene ether and polyamide provides sufficient conductivity to eliminate usage of conductive primers. Additional benefits include improved transfer efficiencies of the primer and top coat systems, uniform film builds across the part, and improved painting of complex geometries.

Several predictive equations based on the chemical composition of gasoline have been shown to estimate the particulate emissions of light-duty, internal combustion engine (ICE) powered vehicles and are reviewed in this paper. Improvements to one of them, the PEISimDis equation are detailed herein. The PEISimDis predictive equation was developed by General Motor’s researchers in 2022 based on two laboratory gas chromatography (GC) analyses; Simulated Distillation (SimDis), ASTM D7096 and Detailed Hydrocarbon Analysis (DHA), ASTM D6730. The DHA method is a gas chromatography mass spectroscopy (GC/MS) methodology and provides the detailed speciation of the hundreds of hydrocarbon species within gasoline. A DHA’s aromatic species from carbon group seven through ten plus (C7 – C10+) can be used to calculate a Particulate Evaluation Index (PEI) of a gasoline, however this technique takes many hours to derive because of its long chromatography analysis time.

This paper describes the design and development of the rear compartment structure of the sixth generation Corvette, C6, which starts in the 2005 model year. The improved design integrates the rear compartment packaging to address issues seen on fifth generation Corvette, C5. The molded composite fiberglass reinforced, tub and surround panels are similar to the C5. These large panels are modified to fit the new styling theme of the C6, while also addressing the packaging requirements of the updated underbody structure and exhaust system. New composite side support brackets and cross car reinforcement combine to address several desired improvements. These side support brackets are designed to package the rear audio speakers, electrical modules, wiring and cable routing while also addressing build variation and localized stiffness improvement. The side brackets support the surround panel increasing the manufacturing control of the surround panel.

This paper introduces a design methodology to tailor the acceleration and displacement responses of a vehicle structure subjected to a dynamic crushing load. The proposed approach is an extension of the hybrid cellular automaton (HCA) method, through which the internal energy density is uniformly distributed within the structure. The proposed approach, referred here to as an extended HCA (xHCA) method, receives the suitable combinations of volume fraction and a finite element meta-parameter for which the algorithm synthesizes the load paths that allow the desired crash response. Lower meta-parameter values lead designs obtained by traditional optimizers, while larger values lead to designs obtained by the HCA method. Simultaneous implementation of multiple values of meta-parameters is presented here as a further development of xHCA method.