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The crush performance of lightweight composite automotive structures varies significantly between static and dynamic test conditions. This paper discusses the development of a new dynamic testing facility that can be used to characterize crash performance at high loads and constant speed. Previous research results from the Energy Management Working Group (EMWG) of the Automotive Composites Consortium (ACC) showed that the static crush resistance of composite tubes can be significantly greater than dynamic crush results at speeds greater than 2 m/s. The new testing facility will provide the unique capability to crush structures at high loads in the intermediate velocity range. A novel machine control system was designed and projections of the machine performance indicate its compliance with the desired test tolerances. The test machine will be part of a national user facility at the Oak Ridge National Laboratory (ORNL) and will be available for use in the summer of 2002.

Traditional Lagrangian spray modeling approaches for internal combustion engines are highly grid-dependent due to insufficient resolution in the near nozzle region. This is primarily because of inherent restrictions of volume fraction with the Lagrangian assumption together with high computational costs associated with small grid sizes. A state-of-the-art grid-convergent spray modeling approach was recently developed and implemented by Senecal et al., (ASME-ICEF2012-92043) in the CONVERGE software. The key features of the methodology include Adaptive Mesh Refinement (AMR), advanced liquid-gas momentum coupling, and improved distribution of the liquid phase, which enables use of cell sizes smaller than the nozzle diameter. This modeling approach was rigorously validated against non-evaporating, evaporating, and reacting data from the literature.

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).

Plug-in hybrid electric vehicle (PHEV) technologies have the potential for considerable petroleum consumption reductions, possibly at the expense of increased tailpipe emissions due to multiple “cold” start events and improper use of the engine for PHEV specific operation. PHEVs operate predominantly as electric vehicles (EVs) with intermittent assist from the engine during high power demands. As a consequence, the engine can be subjected to multiple cold start events. These cold start events may have a significant impact on the tailpipe emissions due to degraded catalyst performance and starting the engine under less than ideal conditions. On current hybrid electric vehicles (HEVs), the first cold start of the engine dictates whether or not the vehicle will pass federal emissions tests. PHEV operation compounds this problem due to infrequent, multiple engine cold starts.

Road vehicles can expend a significant amount of energy in undesirable vertical motions that are induced by road bumps, and much of that is dissipated in conventional shock absorbers as they dampen the vertical motions. Presented in this paper are some of the results of a study aimed at determining the effectiveness of efficiently transforming that energy into electrical power by using optimally designed regenerative electromagnetic shock absorbers. In turn, the electrical power can be used to recharge batteries or other efficient energy storage devices (e.g., flywheels) rather than be dissipated. The results of the study are encouraging - they suggest that a significant amount of the vertical motion energy can be recovered and stored.

A process to recover carbon fibers from obsolete polymer matrix composite (PMC) materials has been developed. Carbon fibers have been recovered from samples containing urethane-based or epoxy-based substrates. An experimental parametric study conducted on both the bench-scale and the pilot-scale has been done to determine the least-cost process conditions. Based on this study, we have evaluated process economics that suggested a payback of about one year. This process is also applicable to polymer matrix composite materials made with thermoplastic substrates. This paper presents the results of the experimental testing campaign and the results of the process economic analysis.

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.

As connectivity and sensing technologies become more mature, automated vehicles can predict future driving situations and utilize this information to drive more energy-efficiently than human-driven vehicles. However, future information beyond the limited connectivity and sensing range is difficult to predict and utilize, limiting the energy-saving potential of energy-efficient driving. Thus, we combine a conventional speed optimization planner, developed in our previous work, and reinforcement learning to propose a real-time intelligent speed optimization planner for connected and automated vehicles. We briefly summarize the conventional speed optimization planner with limited information, based on closed-form energy-optimal solutions, and present its multiple parameters that determine reference speed trajectories.

This work presents a simple fan model that is based on the actuator disk approximation, and the blade element and vortex theory of a propeller. A set of equations are derived that require as input the rotational speed of the fan, geometric fan data, and the lift and drag coefficients of the blades. These equations are solved iteratively to obtain the body forces generated by the fan in the axial and circumferential directions. These forces are used as momentum sources in a CFD code to simulate the effect of the fan in an underhood thermal management simulation. To validate this fan model, a fan experiment was simulated. The model was incorporated into the CFD code STAR-CD and predictions were generated for axial and circumferential air velocities at different radial positions and at different planes downstream of the fan. The agreement between experimental measurements and predictions is good.

Fuel cell-powered electric vehicles (FCPEV) require an energy storage device to start up the fuel cells and to store the energy captured during regenerative braking. Low-voltage (12 V) batteries are preferred as the storage device to maintain compatibility with the majority of today's automobile loads. A dc/dc converter is therefore needed to interface the low-voltage batteries with the fuel cell-powered higher-voltage dc bus system (255 V ∼ 425 V), transferring energy in either direction as required. This paper presents a soft-switched, isolated bi-directional dc/dc converter developed at Oak Ridge National Laboratory for FCPEV applications. The converter employs dual half-bridges interconnected with an isolation transformer to minimize the number of switching devices and their associated gate drive requirements. Snubber capacitors including the parasitic capacitance of the switching devices and the transformer leakage inductance are utilized to achieve zero-voltage switching (ZVS).

Of the fuel cells being studied, the proton exchange membrane fuel cell (PEMFC) is viewed as the most promising for transportation. Yet until today, the commercialization of the PEMFC has not been widespread in spite of its large expectation. Poor long term performances or durability, and high production and maintenance costs account for the main reasons. For the final commercialization of fuel cell in transportation field, the durability issue must be addressed, while the costs should be further brought down. In the meantime, health-monitoring and prognosis techniques are of great significance in ensuring the normal operation of the fuel cell and preventing or predicting its likely abrupt and catastrophic failure. In this paper, an analytical formulation of a damage accumulation law for fuel cell is presented.

Spray behavior is regarded as one of main factors which influence engine performance, fuel consumption and emissions for diesel engine. In practice, spray characteristics from each orifice from a multi-hole nozzle are normally arranged symmetrically, while the hole-to-hole spray variation is unavoidable. This variation will cause spatial uneven distribution of spray and combustion degrade, which will be no longer inconsiderable in face of the more and more stringent emission rules. In this paper, two methods including spray macro-characteristics experiment and separated fuel mass measurement are employed to test the hole-to-hole spray variation of two six-hole symmetric VCO injectors of different brands, and experiments are operated under different conditions including different injection pressures, back pressures and injection durations.

A systems-level modeling framework developed to estimate the life cycle cost of medium- and heavy-duty trucks is discussed in this paper. Costs are estimated at a resolution of five major subsystems and 30+ subsystems, each representing a specific manufacturing technology. Interrelationships among various subsystems affecting cost are accounted for. Results of a specific Class 8 truck are finally discussed to demonstrate the modeling framework's capability, including the analysis of cost-effectiveness of some of the competing alternative system design options being considered by the industry today.

Thermal conductivity detection has long been used in gas chromatography to detect hydrogen and other diatomic gases in a gas sample. Thermal conductivity instruments that are not coupled to gas chromatographs are useful for detecting hydrogen in binary gas mixtures, but suffer from significant cross-interference from other gas species that are separated when the detector is used with a gas chromatograph. This study reports a method for using a commercially-available thermal conductivity instrument to detect and quantify hydrogen in a diesel exhaust stream. The instrument time response of approximately 40 seconds is sufficient for steady-state applications. Cross-interference from relevant gas species are quantified and discussed. Measurement uncertainty associated with the corrections for the various species is estimated and practical implications for use of the instrument and method are discussed.

An alternative approach is presented for the regression of response data on predictor variables that are not logically or physically separable. The methodology is demonstrated by its application to a data set of heavy-duty diesel emissions. Because of the covariance of fuel properties, it is found advantageous to redefine the predictor variables as vectors, in which the original fuel properties are components, rather than as scalars each involving only a single fuel property. The fuel property vectors are defined in such a way that they are mathematically independent and statistically uncorrelated. The available data set is not considered adequate for the development of a full-fledged emission model. Nevertheless, the data clearly show that only a few basic patterns of fuel-property variation affect emissions and that the number of these patterns is considerably less than the number of variables initially thought to be involved.

In order to achieve proposed fuel economy requirements, engines must make better use of the available fuel energy. Regardless of how efficient the engine is, there will still be a significant fraction of the fuel energy that is rejected in the exhaust and coolant streams. One viable technology for recovering this waste heat is an Organic Rankine Cycle. This cycle heats a working fluid using these heat streams and expands the fluid through a turbine to produce shaft power. The present work was the development of such a system applied to a light duty diesel engine. This lab demonstration was designed to maximize the peak brake thermal efficiency of the engine, and the combined system achieved an efficiency of 45%. The design of the system is discussed, as are the experimental performance results. The system potential at typical operating conditions was evaluated to determine the practicality of installing such a system in a vehicle.

Accurate modeling of the internal flow and spray characteristics in fuel injectors is a critical aspect of direct injection engine design. However, such high-fidelity computational fluid dynamics (CFD) models are often computationally expensive due to the requirement of resolving fine temporal and spatial scales. This paper addresses the computational bottleneck issue by proposing a machine learning-based emulator framework, which learns efficient surrogate models for spatiotemporal flow distributions relevant for static coupling injection maps, namely total void fraction, velocity, and mass, within a design space of interest. Different design points involving variations of needle lift, fuel viscosity, and level of non-condensable gas in the fuel were explored in this study. An interpretable Bayesian learning strategy was employed to understand the effect of the design parameters on the void fraction fields at the exit of the injector orifice.

In an effort of providing better understanding of regeneration mechanisms of diesel particulate matter (PM), this experimental investigation focused on evaluating the amount of heat release generated during the thermal reaction of diesel PM and the concentrations of soluble organic compounds (SOCs) dissolved in PM emissions. Differences in oxidation behaviors were observed for two different diesel PM samples: a SOC-containing PM sample and a dry soot sample with no SOCs. Both samples were collected from a cordierite particulate filter membrane in a thermal reactor connected to the exhaust pipe of a light-duty diesel engine. A differential scanning calorimeter (DSC) and a thermogravimetric analyzer (TGA) were used to measure the amount of heat release during oxidation, along with subsequent oxidation rates and the concentrations of SOCs dissolved in particulate samples, respectively.

Battery electric vehicles (BEV) in heavy duty (HD) commercial freight transport face challenging technoeconomic barriers to adoption. Specifically, beyond safety and compliance, fleet and operational logistics require both high up-time and parity with diesel system productivity/Total Cost of Ownership (TCO) to enable strong adoption of electrified powertrains. At present, relatively high energy storage prices coupled with the increased weight of BEV systems limit the practicality of HD commercial freight transport to shorter range applications, where smaller batteries will suffice for the mission energy requirements (single operational shift). This paper presents an approach to extend the feasibility of BEV HD trucking for a broad range of applications.

This work explores pathways to achieve diesel-like, high-efficiency combustion with stoichiometric 3-way catalyst compatible spark ignition (SI). A high stroke-to-bore engine design (1.5:1) with cooled exhaust gas recirculation (EGR) and high compression ratio (rc) was used to improve engine efficiency by up to 30% compared with a production turbocharged gasoline direct injection spark ignition engine. To achieve efficiency improvements, engine experiments were coupled with computational fluid dynamics simulations to guide and explain experimental trends between the original engine and the high stroke-to-bore ratio design (1.5:1). The effects of EGR and late intake valve closing (IVC) and fuel characteristics are investigated through their effects on knock mitigation. Direct injection of 91 RON E10 gasoline, 99 RON E0 gasoline, and liquified petroleum gas (i.e., propane/autogas) were evaluated with geometric rc ranging from 13.3:1 to 16.8:1.