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Modeling plume interaction and collapse for direct-injection gasoline sprays is important because of its impact on fuel-air mixing and engine performance. Nevertheless, the aerodynamic interaction between plumes and the complicated two-phase coupling of the evaporating spray has shown to be notoriously difficult to predict. With the availability of high-speed (100 kHz) Particle Image Velocimetry (PIV) experimental data, we compare velocity field predictions between plumes to observe the full temporal evolution leading up to plume merging and complete spray collapse. The target “Spray G” operating conditions of the Engine Combustion Network (ECN) is the focus of the work, including parametric variations in ambient gas temperature. We apply both LES and RANS spray models in different CFD platforms, outlining features of the spray that are most critical to model in order to predict the correct aerodynamics and fuel-air mixing.

The study of spray-wall interaction is of great importance to understand the dynamics during fuel-surface impingement process in modern internal combustion engines. The identification of droplet post-impingement pattern (contact, transition, non-contact) and droplet characteristics can quantitatively provide an estimation of energy transfer for spray-wall interaction, thus further influencing air-fuel mixing and emissions under combusting conditions. Theoretical criteria of single droplet post-impingement pattern on a dry wall have been experimentally and numerically studied by many researchers to quantify the hydrodynamic droplet behaviors. However, apart from model fidelity, another issue is the scalability. A theoretical criterion developed from one case might not be well suited to another scenario. In this paper, a data-driven approach for single droplet-dry wall post-impingement pattern utilizing arithmetical machine learning classification methods is proposed and demonstrated.

Contemporary manufacturing systems are still evolving. The system elements, layouts, and integration methods are changing continuously, and ‘collaborative robots’ (CoBots) are now being considered as practical industrial solutions. CoBots, unlike traditional CoBots, are safe and flexible enough to work with humans. Although CoBots have the potential to become standard in production systems, there is no strong foundation for systems design and development. The focus of this research is to provide a foundation and four tier framework to facilitate the design, development and integration of CoBots. The framework consists of the system level, work-cell level, machine level, and worker level. Sixty-five percent of traditional robots are installed in the automobile industry and it takes 200 hours to program (and reprogram) them.

Mobility assessment for combat vehicles is often a great challenge for the military due to various subjective attributes. The attributes' characteristics vary significantly depending on the vehicle type and its operating environments such as terrain, weather, and human factors. A clear definition and relationship between multiple attributes including human factors is necessary to assess mobility. To the best of authors' knowledge, many existing mobility assessment techniques use complex analytical methods and focus on individual attributes. In this paper, for the first time, the authors propose a novel approach to define vehicle mobility and its influencing attributes using qualitative linguistic fuzzy variables, which are defined as having values between 0 and 1. The authors also propose a fuzzy logic mobility (FLM) model and a simulation approach to assess a combat vehicle's mobility.

There are many challenges in implementing grid aware plug-in electric vehicle (PEV) charging systems with local load control. New opportunities for innovative load control were created as a result of changes to the 2014 National Electric Code (NEC) about automatic load control definitions for EV charging infrastructure. Stakeholders in optimized dispatch of EV charging assets include the end users (EV drivers), site owner/operators, facility managers and utilities. NEC definition changes allow for ‘over subscription’ of more potential EV charging station load than can be continuously supported if the total load at any time is within the supply system safety limit. Local load control can be implemented via compact submeter(s) with locally hosted control algorithms using direct communication to the managed electric vehicle supply equipment (EVSE).

The 4th Workshop of the Engine Combustion Network (ECN) was held September 5-6, 2015 in Kyoto, Japan. This manuscript presents a summary of the progress in experiments and modeling among ECN contributors leading to a better understanding of soot formation under the ECN “Spray A” configuration and some parametric variants. Relevant published and unpublished work from prior ECN workshops is reviewed. Experiments measuring soot particle size and morphology, soot volume fraction (fv), and transient soot mass have been conducted at various international institutions providing target data for improvements to computational models. Multiple modeling contributions using both the Reynolds Averaged Navier-Stokes (RANS) Equations approach and the Large-Eddy Simulation (LES) approach have been submitted. Among these, various chemical mechanisms, soot models, and turbulence-chemistry interaction (TCI) methodologies have been considered.

A unified approach has been developed and applied to solder joint life prediction in this paper, which indicates a breakthrough for solder joint reliability simulation. It includes the material characterization of solder alloys, the testing of solder joint specimens, a unified viscoplastic constitutive framework with damage evolution, numerical algorithm development and implementation, and experimental validation. The emphasis of this report focuses on the algorithm development and experimental verification of proposed viscoplasticity with damage evolution.

As a result of increasingly stringent regulations and higher customer expectations, auto manufacturers have been considering numerous technology options to improve vehicle fuel economy. Transmissions have been shown to be one of the most cost-effective technologies for improving fuel economy. Over the past couple of years, transmissions have significantly evolved and impacted both performance and fuel efficiency. This study validates the shifting control of advanced automatic transmission technologies in vehicle systems by using Argonne National Laboratory's model-based vehicle simulation tool, Autonomie. Different midsize vehicles, including several with automatic transmission (6-speeds, 7-speeds, and 8-speeds), were tested at Argonne's Advanced Powertrain Research Facility (APRF). For the vehicles, a novel process was used to import test data.

Close coupled catalysts and new ceramic catalyst substrates have significantly improved the light-off performance of automotive converters required to meet stringent emission requirements. The hotter environment of these catalytic converters and the lower structural strength of the ceramic substrates require the rethinking of converter designs. The development of new package requirements to accommodate the change in environment and new substrates are discussed. A historical perspective on converter durability is presented as reference. Development of durability test protocols is essential to verifying product durability performance to these new environments. Data collection and documentation of testing templates are shown to demonstrate the effectiveness of tests that represent real world environments. Design improvements to address failure modes are discussed along with durability improvement results.

The particulate matter (PM) produced from a diesel engine-simulating combustor was characterized in its morphology, microstructure, and fractal geometry by using a unique thermophoretic sampling and Transmission Electron Microscopy (TEM) system. These results revealed that diesel PM produced from the laboratory-scale burner showed similar morphological characteristics to the particulates produced from diesel engines. The flame air/fuel ratio and the particulate temperature history have significant influences on both particle size and fractal geometry. The primary particle sizes were measured to be 14.7 nm and 14.8 nm under stoichiometric and fuel-rich flame conditions, respectively. These primary particle sizes are smaller than those produced from diesel engines. The radii of gyration for the aggregate particles were 83.8 nm and 47.5 nm under these two flame conditions.

During the evolution of Hybrid vehicles as well as electrical vehicles the need for an additional Voltage level was defined for the utilization of high power loads like electrical compressors, electrical heaters as well as power steering and electrical pumps. The main systems benefit is the generation of approximately 12 kW electrical power by a traditional belt driven Generator. This allows boost function for acceleration and recuperation for mild hybrid vehicles with the target to reduce up to 15% CO2 by keeping the traditional thermal based engines. Delphi has developed systems and components that meet the special 48 Volt related electrical requirements on arcing, hot plugging and corrosion. Our benefit is the long term expertise within the total system know how and the derived technical specification and needs.

A KIVA-based CFD tool has been utilized to simulate the effect of a Common-Rail injection system applied to a large, uniflow-scavenged, two-stroke diesel engine. In particular, predictions for variations of injection pressure and injection duration have been validated with experimental data. The computational models have been evaluated according to their predictive capabilities of the combustion behavior reflected by the pressure and heat release rate history and the effects on nitric oxide formation and wall temperature trends. In general, the predicted trends are in good agreement with the experimental observations, thus demonstrating the potential of CFD as a design tool for the development of large diesel engines equipped with Common-Rail injection. Existing deficiencies are identified and can be explained in terms of model limitations, specifically with respect to the description of turbulence and combustion chemistry.

Gasoline is a complex fuel. Many of the constituents of gasoline that are beneficial for the internal combustion engine (ICE) are expected to be challenging for on-board reformers in fuel-cell vehicles. To address these issues, the autothermal reforming of gasoline and individual components of gasoline has been investigated. The results indicate that aromatic components require higher temperatures and longer contact times to reform than paraffinic components. Napthenic components require higher temperatures to reform, but can be reformed at higher space velocities than paraffinic components. The effects of sulfur are dependent on the catalyst. These results suggest that further evolution of gasoline could reduce the demands on the reformer and provide a better fuel for a fuel-cell vehicle.

There is little agreement in the field of driving safety as to how to define cognitive distraction, much less how to measure it. Without a definition and metric, it is impossible to make scientific and engineering progress on determining the extent to which cognitive distraction causes crashes, and ways to mitigate it if it does. We show here that different studies are inconsistent in their definitions of cognitive distraction. For example, some definitions do not include cellular conversation, while others do. Some definitions confound cognitive distraction with visual distraction, or cognitive distraction with cognitive workload. Other studies define cognitive distraction in terms of a state of the driver, and others in terms of tasks that may distract the driver. It is little wonder that some studies find that cognitive distraction is a negligible factor in causing crashes, while others assert that cognitive distraction causes more crashes than drunk driving.

Over the past couple of years, numerous Hybrid Electric Vehicle (HEV) powertrain configurations have been introduced into the marketplace. Currently, the dominant architecture is the power-split configuration, notably the input splits from Toyota Motor Sales and Ford Motor Company. This paper compares two vehicle-level control strategies that have been developed to minimize fuel consumption while maintaining acceptable performance and drive quality. The first control is rules based and was developed on the basis of test data from the Toyota Prius as provided by Argonne National Laboratory's (Argonne's) Advanced Powertrain Research Facility. The second control is based on an instantaneous optimization developed to minimize the system losses at every sample time. This paper describes the algorithms of each control and compares vehicle fuel economy (FE) on several drive cycles.

At 70 miles per hour, overcoming aerodynamic drag represents about 65% of the total energy expenditure for a typical heavy truck vehicle. The goal of this US Department of Energy supported consortium is to establish a clear understanding of the drag producing flow phenomena. This is being accomplished through joint experiments and computations, leading to the intelligent design of drag reducing devices. This paper will describe our objective and approach, provide an overview of our efforts and accomplishments related to drag reduction devices, and offer a brief discussion of our future direction.

The projected frontal area of a vehicle has a significant impact on aerodynamic drag, and thus is an important parameter, for vehicle development, benchmarking, and modeling. However, determining vehicle frontal area can be tedious, time consuming, expensive, or inaccurate. Existing methods include analysis of engineering drawings, vehicle projections, 3D scanners, planimeter measurements from photographs, and estimations using vehicle dimensions. Currently accepted approximation methods can be somewhat unreliable. This study focuses on introducing a method to find vehicle frontal area using digital images and subtraction functions via MATLABs' Image Processing Toolbox. In addition to an overview of the method, this paper describes several variables that were examined to optimize and improve the process such as camera position, surface glare, and vehicle shadow effects.

Evaluations of the dynamic and acoustic responses of panels, partitions, and walls are of concern across many industries, from building home appliances, planning meeting rooms, to designing airplanes and passenger cars. Over the past few decades, search efforts for developing new methodologies and technologies to enable NVH engineers to acquire and correlate dynamically the relationship between input excitations and vibro-acoustic responses of arbitrary-shaped panels has grown exponentially. The application of a particular methodology or technology to the evaluation of a specific structure depends intimately on the goals and objectives of the NVH engineers and industries.

To restrain the phenomenal increase in oil consumption in China, the Chinese government called for measures to reduce oil consumption of the road transportation sector through adopting vehicle fuel consumption standards. This paper describes the development of China's first set of fuel consumption standards for light-duty passenger vehicles. The adopted standards cover M1 class vehicles, which, according to European definition (and adopted by China), include passenger cars, minivans, and sports utility vehicles (SUVs). In particular, we present the goal, technical background, structure, and values of the adopted standards. We also present their potential effect on oil use reduction. The standards are set in liters of fuel consumption per 100 km for individual vehicle weight categories. The standards are maximum fuel consumption values for given vehicle weight categories.

The paper reviews the role of drawbeads in sheet metal stamping. The design of drawbeads is discussed in depth, with treatment of different bead cross sections, bead end shapes, and bead materials. International standards and practices are included. This is followed by the historical development of the modeling of the drawbead restraining force, starting with basic equilibrium approaches, and leading to the use of the finite element method which permits the study of drawbead effects on sheet metal flow in three dimensions. Finally, the potential of active drawbeads is described based upon ongoing research which is directed toward closed-loop computer control of the stamping process through adjustment of the drawbead penetration.