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The Particle Number–Portable Emission Measurement System (PN-PEMS) came into force with Euro VI Phase E regulations starting January 1, 2022. However, positive ignition (PI) engines must comply from January 1, 2024. The delay was due to the unavailability of the PN-PEMS system that could withstand high concentrations of water typically present in the tailpipe (TP) of CNG vehicles, which was detrimental to the PN-PEMS systems. Thus, this study was designed to evaluate the condensation particle counter (CPC)-based PN-PEMS measurement capabilities that was upgraded to endure high concentration of water. The PN-PEMS measurement of solid particle number (SPN23) greater than 23 nm was compared against the laboratory-grade PN systems in four phases. Each phase differs based upon the PN-PEMS and PN system location and measurements were made from three different CNG engines. In the first phase, systems measured the diluted exhaust through constant volume sampler (CVS) tunnel.

Fracture characterization of automotive metals under simple shear deformation is critical for the calibration of advanced fracture models employed in forming and crash simulations. In-plane shear fracture tests of high ductility materials have proved challenging since the sample edge fails first in uniaxial tension before the fracture limit in shear is reached at the center of the gage region. Although through-thickness machining is undesirable, it appears required to promote higher strains within the shear zone. The present study seeks to adapt existing in-plane shear geometries, which have otherwise been successful for many automotive materials, to have a local shear zone with a reduced thickness. It is demonstrated that a novel shear zone with a pocket resembling a “peanut” can promote shear fracture within the shear zone while reducing the risk for edge fracture. An emphasis was placed upon machinability and surface quality for the design of the pocket in the shear zone.

With the capability of avoiding failure in advance, failure prediction model is important not only to end users, but also to the service engineers in vehicle industry. This paper proposes an approach based on anomaly detection algorithms and telematic data to predict the failure of the engine air system with Turbo charger. Firstly, the relationship between air system and all obtained features are analyzed by both physical mechanism and data-wise. Then, the features including altitude, air temperature, engine output power, and charger pressure are selected as the input of the model, with the sampling interval of 1 minute. Based on the selected features, the healthy state for each vehicle is defined by the model as benchmark. Finally, the ‘Medium surface’ is determined for specific vehicle, which is a hyperplane with the medium points of the healthy state located at, to detect the minor weakness symptom (sub-health state).

Driving Automation Systems (DAS) are subject to complex road environments and vehicle behaviors and increasingly rely on sophisticated sensors and Artificial Intelligence (AI). These properties give rise to unique safety faults stemming from specification insufficiencies and technological performance limitations, where sensors and AI introduce errors that vary in magnitude and temporal patterns, posing potential safety risks. The Safety of the Intended Functionality (SOTIF) standard emerges as a promising framework for addressing these concerns, focusing on scenario-based analysis to identify hazardous behaviors and their causes. Although the current standard provides a basic cause-and-effect model and high-level process guidance, it lacks concepts required to identify and evaluate hazardous errors, especially within the context of AI. This paper introduces two key contributions to bridge this gap.

This article analyzes the aerodynamic performance of Class 8 tractor-trailer geometries made available by the Environmental Protection Agency (EPA) using CFD simulation. Large Eddy Simulations (LES) were carried out with the CFD package, Simerics-MP+. A Sleeper tractor and a 53-foot box trailer configuration was considered. The configuration featured a detailed underbody, an open-grille under-hood engine compartment, mirrors, and the radiator and condenser. Multiple tractor-trailer variants were studied by adding aerodynamic surfaces to the baseline geometries. These include tank fairings and side extenders for the cabins, two types of trailer skirts, and a trailer tail. The effect of these devices towards reducing the overall vehicle drag was investigated. Mesh generation was carried out directly on the given geometry, without any surface modifications, using Simerics’ Binary-Tree unstructured mesher.

The steam reforming of CH4 plays a crucial role in the high-temperature activity of natural gas three-way catalysts. Despite existing reports on sulfur inhibition in CH4 steam reforming, there is a limited understanding of sulfur storage and removal dynamics under various lambda conditions. In this study, we utilize a 4-Mode sulfur testing approach to elucidate the dynamics of sulfur storage and removal and their impact on three-way catalyst performance. We also investigate the influence of sulfur on CH4 steam reforming by analyzing CH4 conversions under dithering, rich, and lean reactor conditions. In the 4-Mode sulfur test, saturating the TWC with sulfur at low temperatures emerges as the primary cause of significant three-way catalyst performance degradation. After undergoing a deSOx treatment at 600 °C, NOx conversions were fully restored, while CH4 conversions did not fully recover.

The thermal performance of an engine coolant system is efficient when the engine head temperature is maintained within its optimum working range. For this, it is desired that air should not be entrapped in the coolant system which can lead to localized hot spots at critical locations. However, it is difficult to eliminate the trapped air pockets completely. So, the target is to minimize the entrapped air as much as possible during the coolant filling and deaeration processes, especially in major components such as the radiator, engine head, pump etc. The filling processes and duration are typically optimized in an engine test stand along with design changes for augmenting the coolant filling efficiency. However, it is expensive and time consuming to identify air entrapped locations in tests, decide on the filling strategy and make the design changes in the piping accordingly.

Accurately predicting the future trajectories of surrounding traffic agents is important for ensuring the safety of autonomous vehicles. To address the scenario of frequent interactions among traffic agents in the highway merging area, this paper proposes a trajectory prediction method based on interactive graph attention mechanism. Our approach integrates an interactive graph model to capture the complex interactions among traffic agents as well as the interactions between these agents and the contextual map of the highway merging area. By leveraging this interactive graph model, we establish an agent-agent interactive graph and an agent-map interactive graph. Moreover, we employ Graph Attention Network (GAT) to extract spatial interactions among trajectories, enhancing our predictions. To capture temporal dependencies within trajectories, we employ a Transformer-based multi-head self-attention mechanism.

Shafaat and Kenley in 2015 identified the opportunity to improve System Engineering Standards by incorporating the design principle of learning. The System Level Assessment (SLA) Methodology is an approach that fulfills this need by efficiently capturing the learnings of a team of subject matter experts in the early stages of product system design. By gathering expertise, design considerations are identified that when used with market and business requirements improve the overall quality of the product system. To evaluate the effectiveness of this approach, the methodology has been successfully applied over 400 times within each realm of the New Product Introduction process, including most recently to a Technology Development program (in the earliest stages of the design process) to assess the viability of various electrification technologies under consideration by an automotive Tier 1 supplier.

The Self-Piercing Rivet (SPR) is an effective method for joining aluminum sheets and dissimilar materials. The durability assessment of SPR joints is essential for the optimum design of the automotive body-in-white structure. Fatigue analysis is required for any structural system subject to cyclic loading where durability assessment is required. While there is no established fatigue life prediction model for SPR joints, Rupp’s model is a well-established fatigue life prediction method intended for resistance spot welds. Rupp’s model has been the automotive industry’s choice for fatigue life estimation due to its computational efficiency and ability to capture various loading conditions. The purpose of this study is to investigate the compatibility of Rupp’s model with SPR joints. Load-control fatigue testing was conducted on cross-tension SPR joints of aluminum sheets (Al 6016) with dissimilar thicknesses and SPR joints of dissimilar materials (Al 6016 to DX54D steel).

Diesel oxidation catalyst (DOC) is one of the critical catalyst components in modern diesel aftertreatment systems. It mainly converts unburned hydrocarbon (HC) and CO to CO2 and H2O before they are released to the environment. In addition, it also oxidizes a portion of NO to NO2, which improves the NOx conversion efficiency via fast SCR over the downstream selective catalytic reduction (SCR) catalyst. HC light-off tests, with or without the presence of NOx, has been typically used for DOC evaluation in laboratory. In this work, we aim to understand the influences of DOC light-off experimental conditions, such as initial temperature, initial holding time, HC species, with or without the presence of NOx, on the DOC HC light-off behavior. The results indicate that light-off test with lower initial temperature and longer initial holding time (at its initial temperature) leads to higher DOC light-off temperature.

The prediction accuracy of a three-way catalyst (TWC) model is highly associated with the ability of the model to incorporate the reaction kinetics of the emission process as a lambda function. In this study, we investigated the O2 and H2 concentration profiles of TWC reactions and used them as critical inputs for the development of a global TWC model. We presented the experimental data and global kinetic model showing the impact of thermal degradation on the performance of the TWC. The performance metrics investigated in this study included CH4, NOx, and CO conversions under lean, rich, and dithering light-off conditions to determine the kinetics of oxidation reactions and reduction/reforming/water-gas shift reactions as a function of thermal aging. The O2 and H2 concentrations were measured using mass spectrometry to track the change in the oxidation state of the catalyst and to determine the mechanism of the reactions under these light-off conditions.

Electrical steels are silicon alloyed steels that possess great magnetic properties, making them the ideal material choice for the stator and rotor cores of electric motors. They are typically comprised of laminated stacks of thin electrical steel sheets. An electric motor can reach high temperatures under a heavy load, and it is important to understand the combined effect of temperature and load on the electrical steel’s performance to ensure the long life and safety of electric vehicles. This study investigated the fatigue strength and failure behavior of a 0.27mm thick electrical steel sheet, where the samples were prepared by a stamping process. Stress-control fatigue tests were performed at both room temperature and 150°C. The S-N curve indicated a decrease in the fatigue strength of the samples at the elevated temperature compared to the room temperature by 15-25 MPa in the LCF and HCF regimes, respectively.

Upcoming, stricter diesel exhaust emissions standards will likely require aftertreatment architectures with multiple diesel exhaust fluid (DEF) introduction locations. Managing NH3 slip with technologies such as an ammonia slip catalyst (ASC) will continue to be critical in these future aftertreatment systems. In this study, we evaluate the impact of SO2 exposure on a state-of-the-art commercially available ASC. SO2 is co-fed at 0.5 or 3 ppmv to either approximate or accelerate a real-world exhaust SO2 impact. ASC performance during sulfur co-feeding is measured under a wide variety of simulated real-world conditions. Results indicate that the loss of NO conversion during SCR is dependent on the cumulative SO2 exposure, regardless of the inlet SO2 concentration. Meanwhile, N2O formation under SCR conditions is nonlinearly affected by SO2 exposure, with formation increasing during 0.5 ppmv SO2 exposure but decreasing in the presence of 3 ppmv SO2.

Stoichiometric natural gas engines with three-way catalysts emit less NOx and CH4 due to their higher efficiency compared to lean-burn natural gas engines. Although hydrothermal aging of three-way catalysts has been extensively studied, a deeper understanding beyond hydrothermal aging is needed to explain real-world performance, especially for natural gas engines with near-zero NOx emissions. In this investigation, field-aged three-way catalysts were characterized to identify the contribution of chemical aging to their overall performance. It was found that the sulfur species on the field-aged TWCs were entirely distributed along the catalyst length, showing a decreasing trend, whereas phosphorous contamination was mainly observed at the inlet section of the three-way catalysts, and the phosphorous concentration declined sharply along the axial length.

Plane strain tension is the critical stress state for sheet metal forming because it represents the extremum of the yield function and minima of the forming limit curve and fracture locus. Despite its important role, the stress response in plane strain deformation is routinely overlooked in the calibration of anisotropic plasticity models due to challenges and uncertainty in its characterization. Plane strain tension test specimens used for constitutive characterization typically employ large gage width-to-thickness ratios to promote a homogeneous plane strain stress state. Unfortunately, the specimens are limited to small strain levels due to fracture initiating at the edges in uniaxial tension. In contrast, notched plane strain tension coupons designed for fracture characterization have become common in the automotive industry to calibrate stress-state dependent fracture models. These coupons have significant stress and strain gradients across the gage width to avoid edge fracture.

Commercial automotive diesel engine service and repair, post a diagnostic trouble code trigger, relies on standard troubleshooting steps laid down to identify or narrow down to a faulty engine component. This manual process is cumbersome, time-taking, costly, often leading to incorrect part replacement and most importantly usually associated with significant downtime of the vehicle. Current study aims to address these issues using a novel in-house simulation-based approach developed using a Digital Twin of the engine which is capable of conducting in-mission troubleshooting with real world vehicle/engine data. This cost-effective and computationally efficient solution quickly provides the cause of the trouble code without having to wait for the vehicle to reach the service bay. The simulation is performed with a one-dimensional fluid dynamics, detailed thermodynamics and heat transfer-based diesel engine model utilizing the GT-POWER engine performance tool.

The objective of this study was to assess the formability of two 3rd generation advanced high strength steels (3rd Gen AHSS) with ultimate strengths of 980 and 1180 MPa and evaluate their applicability to a structural B-Pillar for a mid-sized sport utility vehicle. The constitutive behavior including strain-rate effects and formability were characterized to generate the material models for use within AutoForm R8 software to design the B-pillar tooling and forming process. An extended Bressan-Williams instability model was able to deterministically predict the forming limit curves obtained using Marciniak tests. The tooling for the representative B-pillar was designed and fabricated with Bowman Precision Tooling and forming trials conducted for both 3rd Gen steels that had a thickness of 1.4 mm.

Forecasting the motion of the leading vehicle is a critical task for connected autonomous vehicles as it provides an efficient way to model the leading-following vehicle behavior and analyze the interactions. In this study, a personalized time-series modeling approach for leading vehicle trajectory prediction considering different driving styles is proposed. The method enables a precise, personalized trajectory prediction for leading vehicles with limited inter-vehicle communication signals, such as vehicle speed, acceleration, space headway, and time headway of the front vehicles. Based on the learning nature of human beings that a human always tries to solve problems based on grouping and similar experience, three different driving styles are first recognized based on an unsupervised clustering with a Gaussian Mixture Model (GMM).

Residual stress prediction arising from manufacturing processes provides paramount information for the fatigue performance assessment of components subjected to cyclic loading. The determination of the material model to be applied in the numerical model should be taken carefully. This study focuses on the estimation of residual stresses generated after deep rolling of cast iron crankshafts. The researched literature on the field employs the available commercial material codes without closer consideration on their reverse loading capacities. To mitigate this gap, a single element model was used to compare potential material models with tensile-compression experiments. The best fit model was then applied to a previously developed crankshaft deep rolling numerical model. In order to confront the simulation outcomes, residual stresses were measured in two directions on real crankshaft specimens that passed through the same modeled deep rolling process.