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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.

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.

In this multi-phase study, fuel and lubricant effects on stochastic preignition (SPI) were examined. First, the behavior of fuels for which SPI data had previously been collected were characterized in terms of their combustion and emissions behavior, and correlations between these characteristics and their SPI behavior were examined. Second, new SPI data was collected for a matrix of fuels that was constructed to test and confirm hypotheses that resulted from interpretation of the earlier data in the study and from data in open literature. Specifically, the extent to which the presence of heavy components in the fuel affected SPI propensity, and the extent to which flame initiation propensity affected SPI propensity, were examined. Finally, the interaction of fuels with lubricants expected to exhibit a range of SPI propensities was examined.

The introduction of new light-duty vehicle emission limits to comply under real driving conditions (RDE) is pushing the diesel engine manufacturers to identify and improve the technologies and strategies for further emission reduction. The latest technology advancements on the after-treatment systems have permitted to achieve very low emission conformity factors over the RDE, and therefore, the biggest challenge of the diesel engine development is maintaining its competitiveness in the trade-off “CO2-system cost” in comparison to other propulsion systems. In this regard, diesel engines can continue to play an important role, in the short-medium term, to enable cost-effective compliance of CO2-fleet emission targets, either in conventional or hybrid propulsion systems configuration. This is especially true for large-size cars, SUVs and light commercial vehicles.

After-treatment sensors are used in the ECU feedback control to calibrate the engine operating parameters. Due to their contact with exhaust gases, especially NOx sensors are prone to soot deposition with a consequent decay of their performance. Several phenomena occur at the same time leading to sensor contamination: thermophoresis, unburnt hydrocarbons condensation and eddy diffusion of submicron particles. Conversely, soot combustion and shear forces may act in reducing soot deposition. This study proposes a predictive 3D-CFD model for the analysis of the development of soot deposition layer on the sensor surfaces. Alongside with the implementation of deposit and removal mechanisms, the effects on both thermal properties and shape of the surfaces are taken in account. The latter leads to obtain a more accurate and complete modelling of the phenomenon influencing the sensor overall 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.

Carbon, hydrogen and oxygen are major elements in vehicle fuels. Knowledge of fuels elemental composition is helpful in addressing its performance characteristics. Carbon, hydrogen and oxygen composition is an important parameter in engine calibration affecting vehicle performance, emissions and fuel economy. Biodiesel, a fuel comprised of mono-alkyl esters of long-chain fatty acids also known as Fatty Acid Methyl Esters(FAME), derived from vegetable oils or animal fats, has become an important commercial marketplace automotive fuel in the United States (US) and around the world over last few years. FAME biodiesels have many chemical and physical property differences compared to conventional petroleum based diesel fuels. Also, the properties of biodiesel vary based on the feedstock chosen for biodiesel production. One of the key differences between petroleum diesel fuels and biodiesel is the oxygen content.

The new General Motors 2-Mode Hybrid transmission for full-size, full-utility SUVs integrates two electro-mechanical power-split operating modes with four fixed gear ratios and provides fuel savings from electric assist, regenerative braking and low-speed electric vehicle operation. A combination of two power-split modes reduces the amount of mechanical power that must be converted to electricity for continuously variable transmission operation. Four fixed gear ratios further improve power transmission capacity and efficiency for especially demanding maneuvers such as full acceleration, hill climbing, and towing. This paper explains the basics of electro-mechanical power-split transmissions, input-split and compound-split modes, and the addition of fixed gear ratios to these modes to create the 2-Mode Hybrid transmission for SUVs.

Crash safety researchers have an increased concern regarding the decreased thoracic deflection and the contributing injury causation factors among the elderly population. Sternum fractures are categorized as moderate severity injuries, but can have long term effects depending on the fragility and frailty of the occupant. Current research has provided detail on rib morphology, but very little information on sternum morphology, sternum fracture locations, and mechanisms of injury. The objective of this study is two-fold (1) quantify sternum morphology and (2) document sternum fracture locations using computed tomography (CT) scans and crash data. Thoracic CT scans from the University of Michigan Hospital database were used to measure thoracic depth, manubriosternal joint, sternum thickness and bone density. The sternum fracture locations and descriptions were extracted from 63 International Center for Automotive Medicine (ICAM) crash cases, of which 22 cases had corresponding CT scans.

Planetary gear set is one of the most commonly used gear systems in automotive industry as they cater to high power density requirements. A simple planetary gear set consists of a sun gear, ring gear, planets and carrier which houses planet gears. Efficiency of a transmission is dependent upon performance of gear sets involved in power transfer to a great extent. Structural rigidity of a planetary carrier is critical in a planetary gear set as its deflection may alter the load distribution of gears in mesh causing durability and noise issues. Limited studies exist based on geometrical parameters of a carrier which would help a designer in selecting the dimensions at an early stage. In this study, an end to end automated FEA process based on DOE and optimization in Isight is developed. The method incorporates a workflow allowing for an update of carrier geometry, FE model setup, analysis job submission and post-processing of results.

During the early phase of vehicle development, one of the key design attributes to consider is visibility for the driver. Visibility is the ability to see one’s surrounding environment while they are driving. Therefore, it is one of the key requirements to be considered during the vehicle design. Certain vehicle characteristics such as the size of windshield and the design of the pillars influence the perception of visibility for the driver. One specific characteristic influencing satisfaction is A-pillar obscuration and location, which is the subject of this paper. The objective of this project is to analyze the relationship between the A-pillar obscuration/location with the driver satisfaction under real world driving conditions, based on research, statistical data analysis and dynamic clinics. Other influences, such as the position of the occupant in the seat was also studied and captured in this paper.

In recent decades, significant technological advances have made cruise control systems safer, more automated, and available in more driving scenarios. However, comparatively little progress has been made in optimizing vehicle efficiency while in cruise control. In this paper, two distinct strategies are proposed to deliver efficiency benefits in cruise control by leveraging flexibility around the driver’s requested set speed, and road information that is available on-board in many new vehicles. In today’s cruise control systems, substantial energy is wasted by rigidly controlling to a single set speed regardless of the terrain or road conditions. Introducing even a small allowable “error band” around the set speed can allow the propulsion system to operate in a pseudo-steady state manner across most terrain. As long as the vehicle can remain in the allowed speed window, it can maintain a roughly constant load, traveling slower up hills and faster down hills.

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.

This paper discusses an approach to detecting small leaks in an automobile's evaporative emissions systems that is a technique based upon ideal gas laws. It does this by monitoring pressure in the system while the vehicle's engine is off. This low cost solution can be easily implemented on General Motors vehicles using existing components. The topics covered in this paper include details on the background of the problem and the technique, the underlying thermodynamics of the technique, a description of the algorithm, testing and data collection considerations.

Suppliers and integrators are working with SAE’s HM-1 standards team to develop a mechanism to allow “Health Ready Components” to be integrated into larger systems to enable broader IVHM functionality (reference SAE JA6268). This paper will discuss how the design data provided by the supplier of a component/subsystem can be integrated into a vehicle reference model with emphasis on how each aspect of the model is transmitted to minimize ambiguity. The intent is to enhance support for the analytics, diagnostics and prognostics for the embedded component. In addition, we describe functionality being delegated to other system components and that provided by the supplier via syndicated web services. As a specific example, the paper will describe the JA6268 data submittal for a typical automotive turbocharger and other engine air system components to clarify the data modeling and integration processes.

Robustness testing of Advanced Driver Assistance Systems (ADAS) features is a crucial step in ensuring the safety and reliability of these systems. ADAS features include technologies like adaptive cruise control, lateral and longitudinal controls, automatic emergency braking, and more. These systems rely on various sensors, cameras, radar, lidar, and software algorithms to function effectively. Robustness testing aims to identify potential vulnerabilities and weaknesses in these systems under different conditions, ensuring they can handle unexpected scenarios and maintain their performance. Mileage accumulation is one of the validation methods for achieving robustness. It involves subjecting the systems to a wide variety of real-world driving conditions and driving scenarios to ensure the reliability, safety, and effectiveness of the ADAS features.

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 reviews the history of the General Motor's Epsilon Platform from a Body Structure perspective. From the time that it was conceived in 1996 to the present, the platform has evolved to meet many changing requirements. The focus of this paper will cover basic body requirements such as crash performance, modal requirements, packaging issues, changes for wheelbase and powertrains, mass, different body styles, etc, including the differences between European and US requirements. It will demonstrate that this globally developed platform met all its initial requirements and continued to evolve over time to meet additional changing requirements.