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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.

The increasing use of diesel and gasoline particulate filters requires advanced on-board diagnostics (OBD) to prevent and detect filter failures and malfunctions. Early detection of upstream (engine-out) malfunctions is paramount to preventing irreversible damage to downstream aftertreatment system components. Such early detection can mitigate the failure of the particulate filter resulting in the escape of emissions exceeding permissible limits and extend the component life. However, despite best efforts at early detection and filter failure prevention, the OBD system must also be able to detect filter failures when they occur. In this study, radio frequency (RF) sensors were used to directly monitor the particulate filter state of health for both gasoline particulate filter (GPF) and diesel particulate filter (DPF) applications.

A new analytical method to aid in the understanding of the organic carbon (OC) phase of particulate matter (PM) from advanced compression ignition (ACI) operating modes, is presented. The presence of NO2 and unburned fuel aromatics in ACI emissions, and the low exhaust temperatures that result from this low temperature combustion strategy, provide the right conditions for the formation of carboxylic acids and nitroaromatic compounds. These polar compounds contribute to OC in the PM and are not typically measured using nonpolar solvent extraction methods such as the soluble organic fraction (SOF) method. The new extraction and detection method employs capillary electrophoresis with electrospray ionization mass spectrometry (CE-ESI MS) and was specifically developed to determine polar organic compounds in the ACI PM emissions. The new method identified both nitrophenols and aromatic carboxylic acids in the ACI PM.

Fatigue behavior of dissimilar ultrasonic spot welds in lap-shear specimens of magnesium AZ31B-H24 and hot-dipped-galvanized mild steel sheets is investigated based on experimental observations, closed-form stress intensity factor solutions, and a fatigue life estimation model. Fatigue tests were conducted under different load ranges with two load ratios of 0.1 and 0.2. Optical micrographs of the welds after the tests were examined to understand the failure modes of the welds. The micrographs show that the welds mainly fail from kinked fatigue cracks growing through the magnesium sheets. The optical micrographs also indicate that failure mode changes from the partial nugget pullout mode under low-cycle loading conditions to the transverse crack growth mode under high-cycle loading conditions. The closed-form stress intensity factor solutions at the critical locations of the welds are used to explain the locations of fatigue crack initiation and growth.

Failure modes of friction stir spot welds in lap-shear specimens of dissimilar high strength dual phase steel (DP780GA) and hot stamped boron steel (HSBS) sheets are investigated under quasi-static and cyclic loading conditions based on experimental observations. Optical micrographs of dissimilar DP780GA/HSBS friction stir spot welds made by a concave tool before and after failure are examined. The micrographs indicate that the failure modes of the welds under quasi-static and cyclic loading conditions are quite similar. The micrographs show that the DP780GA/HSBS welds mainly fail from cracks growing through the upper DP780GA sheets where the concave tool was plunged into during the welding process. Based on the observed failure modes, a kinked fatigue crack growth model is adopted to estimate fatigue lives.

Friction stir spot welding (FSSW) is applied to join advanced high strength steels (AHSS): galvannealed dual phase 780 MPa steel (DP780GA), transformation induced plasticity 780 MPa steel (TRIP780), and hot-stamped boron steel (HSBS). A low-cost Si₃N₄ ceramic tool was developed and used for making welds in this study instead of polycrystalline cubic boron nitride (PCBN) material used in earlier studies. FSSW has the advantages of solid-state, low-temperature process, and the ability of joining dissimilar grade of steels and thicknesses. Two different tool shoulder geometries, concave with smooth surface and convex with spiral pattern, were used in the study. Welds were made by a 2-step displacement control process with weld time of 4, 6, and 10 seconds. Static tensile lap-shear strength achieved 16.4 kN for DP780GA-HSBS and 13.2 kN for TRIP780-HSBS, above the spot weld strength requirements by AWS. Nugget pull-out was the failure mode of the joint.

Failure mode and fatigue behavior of friction stir spot welds made with convex and concave tools in lap-shear specimens of dissimilar high strength dual phase steel (DP780GA) and hot stamped boron steel (HSBS) sheets are investigated based on experiments and a kinked fatigue crack growth model. Lap-shear specimens with the welds were tested under both quasistatic and cyclic loading conditions. Optical micrographs indicate that under both quasi-static and cyclic loading conditions, the welds mainly fail from cracks growing through the upper DP780GA sheets where the tools were plunged in during the welding processes. Based on the observed failure mode, a kinked fatigue crack growth model is adopted to estimate fatigue lives of the welds. In the kinked crack fatigue crack growth model, the stress intensity factor solutions for fatigue life estimations are based on the closed-form solutions for idealized spot welds in lap-shear specimens.

Development of reliable magnesium (Mg) to steel joining methods is one of the critical issues in broader applications of Mg in automotive body construction. Ultrasonic spot welding (USW) has been demonstrated successfully to join Mg to steel and to achieve strong joints. In this study, corrosion test of ultrasonic spot welds between 1.6 mm thick Mg AZ31B-H24 and 0.8 mm thick galvanized mild steel, without and with adhesive, was conducted. Adhesive used was a one-component, heat-cured epoxy material, and was applied between overlapped sheets before USW. Corrosion test was conducted with an automotive cyclic corrosion test, which includes cyclic exposures of dipping in the 0.5% sodium chloride (NaCl) bath, a constant humidity environment, and a drying period. Lap shear strength of the joints decreased with the cycles of corrosion exposure. Good joint strengths were retained at the end of 30-cycle test.

Failure modes and fatigue behaviors of ultrasonic spot welds in lap-shear specimens of magnesium AZ31B-H24 and hot-dipped-galvanized mild steel sheets with and without adhesive are investigated. Ultrasonic spot welded, adhesive-bonded, and weld-bonded lap-shear specimens were made. These lap-shear specimens were tested under quasi-static and cyclic loading conditions. The ultrasonic spot weld appears not to provide extra strength to the weld-bonded lap-shear specimen under quasi-static and cyclic loading conditions. The quasi-static and fatigue strengths of adhesive-bonded and weld-bonded lap-shear specimens appear to be the same. For the ultrasonic spot welded lap-shear specimens, the optical micrographs indicate that failure mode changes from the partial nugget pullout mode under quasi-static and low-cycle loading conditions to the kinked crack growth mode under high-cycle loading conditions.

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.

In support of the Federal Motor Carrier Safety Administration’s (FMCSA’s) ongoing interest in connected and automated commercial vehicles, this report summarizes analyses conducted to quantify variability in stopping distance tests conducted on commercial truck tractors. The data used were retrieved from tests performed under the controlled conditions specified for FMVSS-121 air brake system compliance testing. The report explores factors affecting the variability of the service brake stopping distance as defined by 49 CFR 571.121, S5.3.1 Stopping Distance—trucks and buses stopping distance. Variables examined in this analysis include brake type, weight, wheelbase, and tractor antilock braking system (ABS). This analysis uses existing test data collected between 2010 and 2019. Several of the examined parameters affected both tractor stopping distance and stopping distance variability.

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.

Large cyclic variability along with increased combustion noise present in low temperature combustion (LTC) modes of internal combustion engines has driven the need for fast response, robust sensors for diagnostics and feedback control. Accelerometers have been shown as a possible technology for diagnostics and feedback control of advanced LTC operation in internal combustion engines. To make better use of this technology, an improved understanding is necessary of the effect of energy release from the combustion process on engine surface vibrations. This study explores the surface acceleration response for a single-cylinder engine operating with homogeneous charge compression ignition (HCCI) combustion. Preliminary investigation of the engine surface accelerations is conducted using a finite element analysis of the engine cylinder jacket along with consideration of cylindrical modes of the engine cylinder.

This paper deals with the effects of various approaches for modeling of strain rate effects for mild and high strength steels (HSS) on impact simulations. The material modeling is discussed in the context of the finite element method (FEM) modeling of progressive crush of energy absorbing automotive components. The characteristics of piecewise linear plasticity strain rate dependent material model are analyzed and various submodels for modeling of impact response of steel structures are investigated. The paper reports on the ranges of strains and strain rates that are calculated in typical FEM models for tube crush and their dependence on the material modeling approaches employed. The models are compared to the experimental results from drop tower tests.

Lean Gasoline Direct Injection (LGDI) combustion is a promising technical path for achieving significant improvements in fuel efficiency while meeting future emissions requirements. Though Stoichiometric Gasoline Direct Injection (SGDI) technology is commercially available in a few vehicles on the American market, LGDI vehicles are not, but can be found in Europe. Oak Ridge National Laboratory (ORNL) obtained a European BMW 1-series fitted with a 2.01 LGDI engine. The vehicle was instrumented and commissioned on a chassis dynamometer. The engine and after-treatment performance and emissions were characterized over US drive cycles (Federal Test Procedure (FTP), the Highway Fuel Economy Test (HFET), and US06 Supplemental Federal Test Procedure (US06)) and steady state mappings. The vehicle micro hybrid features (engine stop-start and intelligent alternator) were benchmarked as well during the course of that study.

Today’s automotive industry is witnessing increasing applications of advanced high strength steels (AHSS) combined with innovative manufacturing techniques to satisfy fuel economy requirements of stringent environmental regulations. The integration of AHSS in novel automotive structure design has introduced huge advantages in mass reduction while maintaining their structural performances, yet several concerns have been raised for this relatively new family of steels. One of those concerns is their potentially high springback after forming, which can lead to geometrical deviation of the final product from its designed geometry and cause difficulties during assembly. From the perspective of accurate prediction, control and compensation of springback, further understanding on the effect of residual stress in AHSS parts is urged. In this work, the residual stress distribution in a 980GEN3 steel part after hydroforming is investigated via experimental and numerical approaches.

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.

We summarize results from comparative simulations of hybrid electric vehicles with either stoichiometric gasoline or diesel engines. Our simulations utilize previously published models of transient engine-out emissions and models of aftertreatment devices for both stoichiometric and lean exhaust. Fuel consumption and emissions were estimated for comparable gasoline and diesel light-duty hybrid electric vehicles operating over single and multiple urban drive cycles. Comparisons between the gasoline and diesel vehicle fuel consumptions and emissions were used to identify potential advantages and technical barriers for diesel hybrids.

Three dimensional fabrics have seen increasing use lately as composite reinforcements. Advantages over prepreg or chopped fiber processes can include cost, handling, consistent quality, impact behavior, and resistance to delamination [1]. To gain acceptance in the transportation industry it is imperative that properties including dynamic and fatigue behavior be designable. A Progressive Failure Analysis (PFA) was developed jointly by Alpha Star Corp and NASA to predict fatigue life of composites and determine their damage mechanisms so that the life could be extended. The title of this software package is GENOA™, and it was used to focus on the three dimensional fabric called 3WEAVE™ made by 3TEX, Inc. It was discovered through fatigue testing that void content greatly affected fatigue life for the 3D E-glass fabric reinforcing a polyurethane modified vinyl ester resin called Dion 9800 from Reichhold. This is a common characteristic for most structural materials.

Composite materials have the potential to reduce the overall cost and weight of automotive structures with the added benefit of being able to dissipate large amounts of impact energy by progressive crushing. To identify and quantify the energy absorbing mechanisms in composite materials, test methodologies were developed for conducting progressive crush tests on composite specimens that have simplified test geometries. The test method development focused on isolating the damage modes associated with the frond formation that occurs in dynamic testing of composite tubes. A new test fixture was designed to progressively crush composite plate specimens under quasi-static test conditions. Preliminary results are presented under a sufficient set of test conditions to validate the operation of the test fixture.