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The question of whether increasing the fuel economy of light-duty natural gas fueled vehicles can improve their economic competitiveness in the U.S. market, and help the US Department of Energy meet stated goals for such vehicles is explored. Key trade-offs concerning costs, exhaust emissions and other issues are presented for a number of possible advanced engine designs. Projections of fuel economy improvements for a wide range of lean-burn engine technologies have been developed. It appears that compression ignition technologies can give the best potential fuel economy, but are less competitive for light-duty vehicles due to high engine cost. Lean-burn spark ignition technologies are more applicable to light-duty vehicles due to lower overall cost. Meeting Ultra-Low Emission Vehicle standards with efficient lean-burn natural gas engines is a key challenge.

This paper presents on-going finite element modeling efforts of friction stir spot welding (FSSW) process using Abaqus/Explicit as a finite element solver. Three-dimensional coupled thermal-stress model was used to calculate thermo-mechanical response of FSSW process. Adaptive meshing and advection schemes, which makes it possible to maintain mesh quality under large deformations, is utilized to simulate the material flow and temperature distribution in FSSW process. The predicted overall deformation shape of the weld joint resembles that experimentally observed. Temperature and stress graphs in the radial direction as well as temperature-deformation distribution plots are presented.

The objective of the research presented in this paper was to assess the influence of stamping process on crash response of UltraLight Steel Auto Body (ULSAB) [1] vehicle. Considered forming effects included thickness variations and plastic strain hardening imparted in the part forming process. The as-formed thickness and plastic strain for front crash parts were used as input data for vehicle crash analysis. Differences in structural performance between crash models with and without forming data were analyzed in order to determine the effects and feasibility of integration of forming processes and crash models.

We utilize physically-based models for diesel exhaust catalytic oxidation and urea-based selective catalytic NOx reduction to study their impact on drive cycle performance of hypothetical light-duty diesel-powered hybrid and plug-in hybrid vehicles (HEVs and PHEVs). The models have been implemented as highly flexible SIMULINK block modules that can be used to study multiple engine-aftertreatment system configurations. The parameters of the NOx reduction model have been adjusted to reflect the characteristics of commercially available Cu-zeolite catalysts, which are of widespread current interest. We demonstrate application of these models using the Powertrain System Analysis Toolkit (PSAT) software for vehicle simulations, along with a previously published methodology that accounts for emissions and temperature transients in the engine exhaust.

It is well known that spark ignited engine performance and efficiency is closely coupled to fuel octane number. The present work combines historical and recent trends in spark ignition engines to build a database of engine design, performance, and fuel octane requirements over the past 80 years. The database consists of engine compression ratio, required fuel octane number, peak mean effective pressure, specific output, and combined unadjusted fuel economy for passenger vehicles and light trucks. Recent trends in engine performance, efficiency, and fuel octane number requirement were used to develop correlations of fuel octane number utilization, performance, specific output. The results show that historically, engine compression ratio and specific output have been strongly coupled to fuel octane number.

Metal additive manufacturing has high potential to produce automobile parts, due to its shape flexibility and unique material properties. On the other hand, residual stress which is generated by rapid solidification causes deformation, cracks and failure under building process. To avoid these problems, understanding of internal residual stress distribution is necessary. However, from the view point of measureable area, conventional residual stress measurement methods such as strain gages and X-ray diffractometers, is limited to only the surface layer of the parts. Therefore, neutron which has a high penetration capability was chosen as a probe to measure internal residual stress in this research. By using time of flight neutron diffraction facility VULCAN at Oak Ridge National Laboratory, residual stress for mono-cylinder head, which were made of aluminum alloy, was measured non-distractively. From the result of precise measurement, interior stress distribution was visualized.

Modeling and simulation of batteries, in conjunction with theory and experiment, are important research tools that offer opportunities for advancement of technologies that are critical to electric motors. The development of data from the application of these tools can provide the basis for managerial and technical decision-making. Together, these will continue to transform batteries for electric vehicles.

The U.S. Government plays an important role in the Partnership for a New Generation of Vehicles' (PNGV) electrical and electronics technologies with a program consisting of high-risk research and development (R&D) projects. The Department of Energy (DOE) plays the largest role in supporting these technologies to specifically address automotive needs. DOE has three Automotive Integrated Power Module (AIPM) contractors and two Automotive Electric Motor Drive (AEMD) contractors working to become viable suppliers for PNGV. Materials development projects are working to improve materials and devices needed in automotive motors and drives, such as permanent magnets, capacitors, sensors, connectors, and thermal management materials. Advancements in inverters, controls, and motors and generators conducted at DOE's national laboratories are also presented.

A prototype emissions control system consisting of a close-coupled lightoff catalyst, catalyzed diesel particle filter (CDPF), and a NOX adsorber was evaluated on a Mercedes A170 CDI. This laboratory experiment aimed to determine whether the benefits of these technologies could be utilized simultaneously to allow a light-duty diesel vehicle to achieve levels called out by U.S. Tier 2 emissions legislation. This research was carried out by driving the A170 through the U.S. Federal Test Procedure (FTP), US06, and highway fuel economy test (HFET) dynamometer driving schedules. The vehicle was fueled with a 3-ppm ultra-low sulfur fuel. Regeneration of the NOX adsorber/CDPF system was accomplished by using a laboratory in-pipe synthesis gas injection system to simulate the capabilities of advanced engine controls to produce suitable exhaust conditions. The results show that these technologies can be combined to provide high pollutant reduction efficiencies in excess of 90% for NOX and PM.

Increases in efficiency may be possible by a new technique for non-thermal plasma aftertreatment of exhaust gases. The new technique involves very short risetimes (40ps) high frequency (5Ghz) high power bursts of low duty factor microwaves to generate a dielectric barrier discharge. The technique is illustrated in the simplified example of the dissociation of NO in N2. Electric field distributions and enhancing improvements are briefly described for a number of configurations. The technique is meant to be used in conjunction with material catalyst and can, for a class of catalysts, cause a significant reactivity on the catalyst surface.

The computer-aided-design and analysis of a robust casting process requires the optimization of both mold filling and solidification. A number of commercial casting codes are available for modeling the fluid flow during mold filling and the heat transfer during solidification. The next generation casting process models will build on present capabilities to allow the prediction of microporosity and other defects and microstructure. This paper will discuss the issues involved in the development of next generation casting process models and present results from a computer model for microporosity prediction that is based on first principles, and will take into account alloy composition, alloy microstructure, the initial hydrogen content of the liquid alloy, and the resistance to inter-dendritic fluid flow to feed shrinkage.

An operational challenge associated with SCR catalysts is the NH3 slip control, particularly for commercial small pore Cu-zeolite formulations as a consequence of their significant ammonia storage capacity. The desorption of NH3 during increasing temperature transients is one example of this challenge. Ammonia slipping from SCR catalyst typically passes through a platinum based ammonia oxidation catalyst (AMOx), leading to the formation of the undesired byproducts NOx and N2O. We have discovered a distinctive characteristic, an overlapping NH3 desorption and oxidation, in a state-of-the-art Cu-zeolite SCR catalyst that can minimize NH3 slip during temperature transients encountered in real-world operation of a vehicle.

Neutron diffraction is a powerful tool that can be used to identify the phases present and to measure the spacing of the atomic planes in a material. Thus, the residual stresses can be determined within a component and/or the phases present. New intercritically austempered irons rely on the unique properties of the austenite phase present in their microstructures. If these materials are to see widespread use, methods to verify the quality (behavior consistency) of these materials and to provide guidance for further optimization will be needed. Neutron diffraction studies were performed at the second generation neutron residual stress facility (NRSF2) at the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory on a variety of intercritically austempered irons. For similar materials, such as TRIP steels, the strengthening mechanism involves the transformation of metastable austenite to martensite during deformation.

Driver is a key component in vehicle simulation. An ideal driver model simulates driving patterns a human driver may perform to negotiate road profiles. There are simulation packages having the capability to simulate driver behavior. However, it is rarely documented how they work with road profiles. This paper proposes a new truck driver model for vehicle simulation to imitate actual driving behavior in negotiating road grade and curvature. The proposed model is developed based upon Gipps' car-following model. Road grade and curvature were not considered in the original Gipps' model although it is based directly on driver behavior and expectancy for vehicles in a stream of traffic. New parameters are introduced to capture drivers' choice of desired speeds that they intend to use in order to negotiating road grade and curvature simultaneously. With the new parameters, the proposed model can emulate behaviors like uphill preparation for different truck drivers.

Several standard methods exist for testing composites, metals and plastics in Mode I fracture. However, these standard test methods have limitations that disqualify them as candidates for testing certain automotive materials. In order to conduct successful fracture toughness tests with these automotive materials, a modified double cantilever beam testing geometry and associated new procedure have been developed. Both the test procedure and the data analysis have been fully documented in a draft standard. Representative SRIM composite, e-coat steel and epoxy were selected to develop and validate the testing procedure.

Metal Compression Forming (MCF) is a variant of the squeeze casting process, in which molten metal is allowed to solidify under pressure in order to close porosity and form a sound part. However, the MCF process applies pressure on the entire mold face, thereby directing pressure on all regions of the casting and producing a uniformly sound part. The process is capable of producing parts with properties close to those of forgings, while retaining the near net shape, complexity in geometry, and relatively low cost of the casting process. The paper describes the casting process development involved in the production of an aluminum A357 alloy motor mount bracket, including the use of a filling and solidification model to design the gating and determine process parameters. Tensile properties of the component are presented and correlated with those of forged components.

China's plug-in electric vehicle (PEV) market with stocks at 7.8 million is the world's largest in 2021, and it accounts for half of the global PEV growth in 2021. The PEV market in China has dramatically evolved since the pandemic in 2020: over 20% of all new PEV sales are from China by mid-2022. Recent features of PEV market dynamics, consumer acceptance, policies, and infrastructure have important implications for both the global energy market and manufacturing stakeholders. From the perspective of demand pull-supply push, this study analyzes China's PEV industry with a market dynamics framework by reviewing sales, product and brand, infrastructure, and government policies from the last few years and outlooking the development of the new government’s 14th Five-Year Plan (2021-2025).

Advanced lightweight materials are increasingly being incorporated into new vehicle designs by automakers to enhance performance and assist in complying with increasing requirements of corporate average fuel economy standards. To assess the primary energy and carbon dioxide equivalent (CO2e) implications of vehicle designs utilizing these materials, this study examines the potential life cycle impacts of two lightweight material alternative vehicle designs, i.e., steel and aluminum of a typical passenger vehicle operated today in North America. LCA for three common alternative lightweight vehicle designs are evaluated: current production (“Baseline”), an advanced high strength steel and aluminum design (“LWSV”), and an aluminum-intensive design (AIV). This study focuses on body-in-white and closures since these are the largest automotive systems by weight accounting for approximately 40% of total curb weight of a typical passenger vehicle.

A transient, one-dimensional lean NOx trap (LNT) model is described and implemented for vehicle systems simulations. The model accounts for conservation of chemical species and thermal energy, and includes the effects of O₂ storage and NOx storage (in the form of nitrites and nitrates). Nitrites and nitrates are formed by diffusion of NO and NO₂, respectively, into sorbent particles, and reaction rates are controlled by chemical kinetics and solid-phase diffusion. The model also accounts for thermal aging and sulfation by means of empirical correlations, which have been derived from laboratory experiments. Example simulation results using the Powertrain Systems Analysis Toolkit (PSAT) are presented.

Current artificial intelligence techniques for end to end driving of autonomous vehicles typically rely on a single form of learning or training processes along with a corresponding dataset or simulation environment. Relatively speaking, success has been shown for a variety of learning modalities in which it can be shown that the machine can successfully “drive” a vehicle. However, the realm of real-world driving extends significantly beyond the realm of limited test environments for machine training. This creates an enormous gap in capability between these two realms. With their superior neural network structures and learning capabilities, humans can be easily trained within a short period of time to proceed from limited test environments to real world driving.