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Abstract The ASTM D130 was first issued in 1922 as a tentative standard for the detection of corrosive sulfur in gasoline. A clean copper strip was immersed in a sample of gasoline for three hours at 50°C with any corrosion or discoloration taken to indicate the presence of corrosive sulfur. Since that time, the method has undergone many revisions and has been applied to many petroleum products. Today, the ASTM D130 standard is the leading method used to determine the corrosiveness of various fuels, lubricants, and other hydrocarbon-based solutions to copper. The end-of-test strips are ranked using the ASTM Copper Strip Corrosion Standard Adjunct, a colored reproduction of copper strips characteristic of various degrees of sulfur-induced tarnish and corrosion, first introduced in 1954. This pragmatic approach to assessing potential corrosion concerns with copper hardware has served various industries well for a century.

Abstract This work presents a generalized methodology for the optimal thermal management of different powertrain devices. The methodology is based on the adoption of an electrically driven pump and on the development of a specifically designed controller algorithm. This is achieved following a Model Predictive Control approach and requires a generalized lumped-parameters model of the thermal exchange between the device walls and the coolant. The methodology is validated at a test rig, with reference to a four-cylinder spark-ignition engine. Results show that the proposed approach allows a reduction in fuel consumption of about 2-3% during the engine warm-up, a decrease in fuel consumption of about 1-2% during fully warmed operation, and an estimated fuel consumption reduction of about 2.5-3% in an NEDC. Finally, the investigation highlights that the proposed approach reduces the risk of after-boiling when the engine is rapidly switched off after a prolonged high-load operation.

Abstract It is widely understood that the thermal state of a light-duty vehicle at the beginning of a trip influences the vehicle performance throughout the drive cycle. Cold starts, or initial states with component temperatures near ambient conditions, are strongly correlated with reduced vehicle performance and energy efficiency and increased emissions. Despite this understanding, there is little literature available that characterizes initial thermal states beyond empirical studies and simplified analyses of dwell times. We introduce a framework that considers vehicle activity patterns, including the previous drive event, duration of the previous dwell event, and relevant ambient conditions occurring during these events. Moreover, the framework allows for technologies to influence the prominence of cold starts and warm starts.

Abstract The United Nation Economic Commission for Europe (UNECE) Regulation 155—Cybersecurity and Cybersecurity Management System (UN R155) mandates the development of cybersecurity management systems (CSMS) as part of a vehicle’s lifecycle. An inherent component of the CSMS is cybersecurity risk management and assessment. Validation and verification testing is a key activity for measuring the effectiveness of risk management, and it is mandated by UN R155 for type approval. Due to the focus of R155 and its suggested implementation guideline, ISO/SAE 21434:2021—Road Vehicle Cybersecurity Engineering, mainly centering on the alignment of cybersecurity risk management to the vehicle development lifecycle, there is a gap in knowledge of proscribed activities for validation and verification testing.

Abstract This article proposes a novel approach of a hybrid system of physics and data-driven modeling for accurately estimating the state of charge (SOC) of a battery. State of Charge (SOC) is a measure of the remaining battery capacity and plays a significant role in various vehicle applications like charger control and driving range predictions. Hence the accuracy of the SOC is a major area of interest in the automotive sector. The method proposed in this work takes the state-of-the-art practice of Kalman filter (KF) and merges it with intelligent capabilities of machine learning using neural networks (NNs). The proposed hybrid system comprises a physics-based battery model and a plurality of NNs eliminating the need for the conventional KF while retaining its features of the predictor-corrector mechanism of the variables to reduce the errors in estimation.

Abstract With the introduction of advanced lightweight materials with complex microstructures and behaviors, more focus is put on the accurate determination of their forming limits, and that can only be possible through experiments as the conventional theoretical models for the forming limit curve (FLC) prediction fail to perform. Despite that, CAE engineers, designers, and toolmakers still rely heavily on theoretical models due to the steep costs associated with formability testing, including mechanical setup, a large number of tests, and the cost of a stereo digital image correlation (DIC) system. The international standard ISO 12004-2:2021 recommends using a stereo DIC system for formability testing since two-dimensional (2D) DIC systems are considered incapable of producing reliable strains due to errors associated with out-of-plane motion and deformation.

Abstract The 2010 Environmental Protection Agency (EPA) Emission Standard for heavy-duty engines required 0.2 g/bhp-hr over certification cycles (cold and hot Federal Test Procedure [FTP]), and the California Air Resources Board (CARB) standards require 0.02 g/bhp-hr for the same cycles leading to a 90% reduction of overall oxides of nitrogen (NOx) emissions. Similar reductions may be considered by the EPA through its Cleaner Trucks Initiative program. In this article, aftertreatment system components consisting of a diesel oxidation catalyst (DOC); a selective catalytic reduction (SCR) catalyst on a diesel particulate filter (DPF), or SCR-F; a second DOC (DOC2); and a SCR along with two urea injectors have been analyzed, which could be part of an aftertreatment system that can achieve the 0.02 g/bhp-hr standard.

Abstract Autonomy is a key enabling factor in uncrewed aircraft system (UAS) and advanced air mobility (AAM) applications ranging from cargo delivery to structure inspection to passenger transport, across multiple sectors. In addition to guiding the UAS, autonomy will ensure that they stay safe in a large number of off-nominal situations without requiring the operator to intervene. While the addition of autonomy enables the safety case for the overall operation, there is a question as to how we can assure that the autonomy itself will work as intended. Specifically, we need assurable technical approaches, operational considerations, and a framework to develop, test, maintain, and improve these capabilities. We make the case that many of the key autonomy functions can be realized in the near term with readily assurable, even certifiable, design approaches and assurance methods, combined with risk mitigations and strategically defined concepts of operations.

Abstract Heavy-duty (HD) diesel engines are the primary propulsion systems in use within the transportation sector and are subjected to stringent oxides of nitrogen (NOx) and particulate matter (PM) emission regulations. The objective of this study is to develop a robust calibration technique to optimize HD diesel engine for performance and emissions to meet current and future emissions standards during certification and real-world operations. In recent years, California - Air Resources Board (C-ARB) has initiated many studies to assess the technology road maps to achieve Ultra-Low NOx emissions for HD diesel applications [1]. Subsequently, there is also a major push for the complex real-world driving emissions as the confirmatory and certification testing procedure in Europe and Asia through the UN-ECE and ISO standards.

Abstract The demand for contactless, rapid manufacturing has increased over the years, especially during the COVID-19 pandemic. Additive manufacturing (AM), a type of rapid manufacturing, is a computer-based system that precisely manufactures products. It proves to be a faster, cheaper, and more efficient production system when integrated with cloud-based manufacturing (CBM). Similarly, the need for semiconductors has grown exponentially over the last five years. Several companies could not keep up with the increasing demand for many reasons. One of the main reasons is the lack of a workforce due to the COVID-19 protocols. This article proposes a novel technique to manufacture semiconductor chips in a fast-paced manner. An algorithm is integrated with cloud, machine vision, sensors, and email access to monitor with live feedback and correct the manufacturing in case of an anomaly.

Abstract The braking phenomenon is an aspect of vehicle stopping performance where with kinetic energy due to the speed of the vehicle is transformed into thermal energy produced by the brake disc and its pads. The heat must then be dissipated into the surrounding structure and into the airflow around the brake system. The thermal friction field during the braking phase between the disc and the brake pads can lead to excessive temperatures. In our work, we presented numerical modeling using ANSYS software adapted in the finite element method (FEM), to follow the evolution of the global temperatures for the two types of brake discs, full and ventilated disc during braking scenario. Also, numerical simulation of the transient thermal analysis and the static structural analysis were performed here sequentially, with coupled thermo-structural method.

Abstract Safety is always a crucial aspect of developing autonomous systems, and the motivation behind this project comes from the need to address the traffic crashes occurring globally on a daily basis. The present work studies the coexistence of the novel rule-based behavioral planning framework with the five key advanced driver assistance system (ADAS) features as proposed in this article to fulfill the safety requirements and enhance the comfort of the driver/passengers to achieve a receding-horizon autopilot. This architecture utilizes data from the sensor fusion and the prediction module for the prediction time horizon of 2 s iteratively, which is continuously moving forward (hence, the receding horizon), and helps the behavior planner understand the intent of other vehicles on the road in advance.

Abstract In this work, the refinement of a phenomenological turbulence model developed in recent years by the authors is presented in detail. As known, reliable information about the underlying turbulence intensity is a mandatory prerequisite to predict the burning rate in phenomenological combustion models. The model is embedded under the form of “user routine” in the GT-Power™ software. The main advance of the proposed approach is the potential to describe the effects on the in-cylinder turbulence of some geometrical parameters, such as the intake runner orientation, the compression ratio, the bore-to-stroke ratio, and the valve number. The model is based on three balance equations, referring to the mean flow kinetic energy, the tumble vortex momentum, and the turbulent kinetic energy (3-eq. concept). An extended formulation is also proposed, which includes a fourth equation for the dissipation rate, allowing to forecast also the integral length scale (4-eq. concept).

Abstract A wind-tunnel study was undertaken to investigate the drag reduction potential of two-truck platooning, in the context of understanding some of the factors that may influence the potential fuel savings and greenhouse-gas reductions. Testing was undertaken in the National Research Council Canada 2 m × 3 m Wind Tunnel with two 1/15-scale models of modern aerodynamic tractors paired with dry-van trailers configured with and without combinations of side-skirts and boat-tails. Separation distances of 0.14, 0.28, 0.49, 0.70 and 1.04 vehicle lengths were tested (3 m, 6 m, 10.5 m, 15 m, and 22.5 m full scale). Additionally, within-lane lateral offsets up to 0.31 vehicle widths (0.8 m full scale) were evaluated, along with a full-lane offset of 1.42 vehicle widths (3.7 m full scale). This study has made use of a wind-averaged-drag coefficient as the primary metric for evaluating the effect of vehicle platooning.

Abstract In this work, an in situ multispecies portable emission measurement system (PEMS) is presented. The system is based on tunable diode laser absorption spectroscopy (TDLAS) and is capable of measuring tailpipe emissions without the necessity of online calibration. It is intended for application on passenger cars within the real drive emission (RDE) procedure of the Worldwide Harmonized Light Duty Test Procedure (WLTP). In contrast to the extractive measurement principles of commercially available PEMS, the introduced measurement system does not require gas sampling or preconditioning and thus does not suffer from the same low-pass filter effects on the measurements. These differences are suspected to have an impact on certification-relevant measurement data. Measurements have been conducted on a 3-cylinder 1 liter EURO 6 b gasoline engine test bench to investigate the differences between the presented measurement system and a commercially available PEMS.

Abstract In this article, a methodology is presented to assess the influence of time-averaged deformations on a production car of the 2018 A-class due to wind load. Exemplary, the deformations of the front and rear bumper are investigated. The aerodynamic development of vehicles at Mercedes-Benz is divided into several phases. When comparing, force coefficients differences can be observed between these distinct hardware stages as well as when comparing steady-state simulations to wind tunnel measurements. In early phases when prototype vehicles are not yet available, so-called aero foam models are used. These are well-defined full-sized vehicle models as the outer skin is milled from Polyurethane. Important aerodynamic characteristics such as an engine compartment with a cooling module, deflecting axles with rotatable wheels, and underbody covers are represented.

Abstract An innovative analysis approach to evaluate heavy-duty vehicle downhill engine brake performance was developed. The vehicle model developed with GT-Drive simulates vehicle downhill control speeds with different engine brake retarding powers, transmission gears, and vehicle weights at sea level or high altitude. The outputs are then used to construct multi-factor parametric design charts. The charts can be used to analyze the vehicle-level engine brake capabilities or compare braking performance difference between different engine brake configurations to quantify the risk of engine retarding power deficiency at both sea level and high altitude downhill driving conditions.

Abstract The inspection process of non-rigid parts during manufacturing and assembly is inherently challenging. This is exacerbated by the need for accurate real-time part data in the digital age. Although many ad hoc techniques exist, there are no rigorous methods to evaluate the quality of a fixture layout before final parts and gauges are available. This typically happens so late in the manufacturing process that errors found can scarcely be remedied. Additionally, the modifications to the gauge are usually costly and can result in significant delays, when performed this late in the process. This article proposes an optimization-driven mathematical approach tailored toward non-rigid parts to identify the best locator layout, early in the part design phase. A metric is proposed using robotic grasping theory to quantify the quality of the locating scheme and serves as the objective of optimization.

Abstract In this article, the method based on the combination of the acoustic perturbation equations and the statistical energy analysis has been used to simulate and optimize the interior aerodynamic noise of a large sport utility vehicle model. The reliability of the method was verified by comparing the analysis results with the wind tunnel test. Influenced by the main noise sources such as A-pillar, exterior rearview mirror, and front sidewindow, the wind noise of the model was significantly greater than that of the same class. To improve the wind noise performance, the side mirror was optimized with the method, including the minimum distance between the rearview mirror and the triangle trim cover, the angle between the rearview mirror and the front sidewindow, and the shell groove of the rearview mirror. The simulation results show that the overall sound pressure level in the car decreases by 2.12 dBA and the articulation index increases by 4.04% after optimization.

Abstract The variation of inflation pressure has an important effect on the longitudinal slip characteristics of tires that can affect the braking performance of the vehicle, so the influence of inflation pressure should be taken into account in high-precision tire models. However, the effects of inflation pressure and vertical load on tire force and moment characteristics are usually coupled. When the inflation pressure is changing while keeping the load constant, the tire contact patch and carcass stiffness will change at the same time, so the contribution of tread and carcass to tire traction properties cannot be decoupled so that the tire design cannot be well guided. On the contrary, if the vertical loading method is changed, the vertical deflection control is used instead of load control.