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With nearly 220,000 vehicles, the United States Postal Service (USPS) has the largest non-military vehicle fleet in the world. This fleet requires over a billion dollars of fuel annually, and this figure does not include contracted vehicles. As a part of the business strategy, the USPS has embraced and invested in alternative fueled vehicles since 1899, when the first recorded use of an electric vehicle for USPS service was performed as a technology evaluation in Cleveland, OH. As part of a technology evaluation of advanced vehicle systems, the USPS has partnered with the DOE?s Vehicle Technology Program (VTP) to benchmark and quantify the capabilities of five vehicles in meeting specific Urban Route Delivery requirements, both with dynamometer and in-service testing. The all electric vehicle conversions have been developed by established electric vehicle systems manufacturers representing various perspectives on meeting the vehicle specific operation objectives.

Continuous efforts to develop a lightweight alloy suitable for the most demanding applications in automotive industry resulted in a number of advanced aluminum (Al) and magnesium alloys and manufacturing routes. One example of this is the application of 319 Al alloy for production of 3.6L V6 gasoline engine blocks. Aluminum is sand cast around Fe-liner cylinder inserts, prior to undergoing the T7 heat treatment process. One of the critical factors determining the quality of the final product is the type, level, and profile of residual stresses along the Fe liners (or extent of liner distortion) that are always present in a cast component. In this study, neutron diffraction was used to characterize residual stresses along the Al and the Fe liners in the web region of the cast engine block. The strains were measured both in Al and Fe in hoop, radial, and axial orientations. The stresses were subsequently determined using generalized Hooke's law.

The CRC Fuels for Advanced Combustion Engines working group has worked to identify a matrix of research diesel fuels for use in advanced combustion research applications. Nine fuels were specified and formulated to investigate the effects of cetane number aromatic content and 90% distillation fraction. Standard ASTM analyses were performed on the fuels as well as GC/MS and1H/13C NMR analyses and thermodynamic characterizations. Details of the actual results of the fuel formulations compared with the design values are presented, as well as results from standard analyses, such as heating value, viscosity and density. Cetane number characterizations were accomplished by using both the engine method and the Ignition Quality Tester (IQT™) apparatus.

Ultrasonic spot welds were made between sheets of 0.8-mm-thick hot-dip-galvanized mild steel and 1.6-mm-thick AZ31B-H24. Lap-shear strengths of 3.0-4.2 kN were achieved with weld times of 0.3-1.2 s. Failure to achieve strong bonding of joints where the Zn coating was removed from the steel surface indicate that Zn is essential to the bonding mechanism. Microstructure characterization and microchemical analysis indicated temperatures at the AZ31-steel interfaces reached at least 344°C in less than 0.3 s. The elevated temperature conditions promoted annealing of the AZ31-H24 metal and chemical reactions between it and the Zn coating.

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.

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.

Electric drives, whether in battery electric vehicles (BEVs) or various other applications, are an important part of modern transportation. Traditionally, physics-based models based on steady-state mapping of electric drives have been used to evaluate their behavior under transient conditions. Hardware-in-the-Loop (HIL) testing seeks to provide a more accurate representation of a component’s behavior under transient load conditions that are more representative of real world conditions it will operate under, without requiring a full vehicle installation. Oak Ridge National Laboratory (ORNL) developed such a HIL test platform capable of subjecting electric drives to both conventional steady-state test procedures as well as transient experiments such as vehicle drive cycles.

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.

This paper introduces a promising approach for developing an integrated traction motor drive based on the Integrated Modular Motor Drive (IMMD) concept. The IMMD concept strives to meet aggressive power density and performance targets by modularizing both the machine and power electronics and then integrating them into a single combined machine-plus-drive structure. Physical integration of the power electronics inside the machine makes it highly desirable to increase the power electronics operating temperature including higher power semiconductor junction temperatures and improved device packaging. Recent progress towards implementing the IMMD concept in an integrated traction motor drive is summarized in this paper. Several candidate permanent magnet (PM) machine configurations with different numbers of phases between 3 and 6 are analyzed to compare their performance characteristics and key application features.

To provide useful information for automakers to design successful plug-in hybrid electric vehicle (PHEV) products and for energy and environmental analysts to understand the social impact of PHEVs, this paper addresses the question of how many of the U.S. consumers, if buying a PHEV, would prefer what electric ranges. The Market-oriented Optimal Range for PHEV (MOR-PHEV) model is developed to optimize the PHEV electric range for each of 36,664 sampled individuals representing U.S. new vehicle drivers. The optimization objective is the minimization of the sum of costs on battery, gasoline, electricity and refueling hassle.

The CRC Fuels for Advanced Combustion Engines (FACE) Working Group has provided a matrix of experimental diesel fuels for use in studies on the effects of three parameters, Cetane number (CN), aromatics content, and 90 vol% distillation temperature (T90), on combustion and emissions characteristics of advanced combustion strategies. Various types of fuel analyses and engine experiments were performed in well-known research institutes. This paper reviews a collection of research findings obtained with these nine fuels. An extensive collection of analyses were performed by members of the FACE working group on the FACE diesel fuels as a means of aiding in understanding the linkage between fuel properties and combustion and emissions performance. These analyses included non-traditional chemical techniques as well as established ASTM tests. In a few cases, both ASTM tests and advanced analyses agreed that some design variables differed from their target values when the fuels were produced.

Plug-in hybrid electric vehicles (PHEV) operate predominantly as electric vehicles (EV) with intermittent assist from the engine. As a consequence, the engine can be subjected to multiple cold start events. These cold start events have a significant impact on tailpipe emissions due to degraded catalyst performance and starting the engine under less than ideal conditions. On current conventional vehicles, 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. ORNL, in collaboration with the University of Tennessee, developed an Engine-In-the-Loop (EIL) test platform to investigate cold start emissions on a 2.0l Gasoline Turbocharged Direct Injection (GTDI) Ecotec engine coupled to a virtual series hybrid electric vehicle.

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.

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.

Advanced lightweight materials are increasingly being incorporated into new vehicle designs by automakers to enhance performance and assist in complying with increasing requirements of corporate average fuel economy standards. To assess the primary energy and carbon dioxide equivalent (CO2e) implications of vehicle designs utilizing these materials, this study examines the potential life cycle impacts of two lightweight material alternative vehicle designs, i.e., steel and aluminum of a typical passenger vehicle operated today in North America. LCA for three common alternative lightweight vehicle designs are evaluated: current production (“Baseline”), an advanced high strength steel and aluminum design (“LWSV”), and an aluminum-intensive design (AIV). This study focuses on body-in-white and closures since these are the largest automotive systems by weight accounting for approximately 40% of total curb weight of a typical passenger vehicle.

For renewable fuels to displace petroleum, they must be compatible with emissions control devices. Pure biodiesel contains up to 5 ppm Na + K and 5 ppm Ca + Mg metals, which have the potential to degrade diesel emissions control systems. This study aims to address these concerns, identify deactivation mechanisms, and determine if a lower limit is needed. Accelerated aging of a production exhaust system was conducted on an engine test stand over 1001 h using 20% biodiesel blended into ultra-low sulfur diesel (B20) doped with 14 ppm Na. This Na level is equivalent to exposure to Na at the uppermost expected B100 value in a B20 blend for the system full-useful life. During the study, NOx emissions exceeded the engine certification limit of 0.33 g/bhp-hr before the 435,000-mile requirement.

Small impurities in the fuel can have a significant impact on the emissions control system performance over the lifetime of the vehicle. Of particular interest in recent studies has been the impact of sodium, potassium, and calcium that can be introduced either through fuel constituents, such as biodiesel, or as lubricant additives. In a collaboration between the National Renewable Energy Laboratory and the Oak Ridge National Laboratory, a series of accelerated aging studies have been performed to understand the potential impact of these metals on the emissions control system. This paper explores the effect of the rate of accelerated aging on the capture of fuel-borne metal impurities in the emission control devices and the subsequent impact on performance. Aging was accelerated by doping the fuel with high levels of the metals of interest. Three separate evaluations were performed, each with a different rate of accelerated aging.

The effect of B and Si additions on fracture and fatigue performance of vacuum carburized 4320 steel and modifications of 4320 steel containing additions of Si (1.0 and 2.0 wt pct) and B (0 and 17 ppm) was evaluated by bending fatigue testing. Three rates of gas quenching, in 10 bar nitrogen and 15 and 20 bar helium, were used to cool specimens after carburizing. The B, protected by Ti additions, together with the Si additions, increased core hardenability. The B/Si modified steels showed no improvement in fatigue resistance, as measured by endurance limits established by 10 million cycle runouts without fracture. However, scanning electron microscopy showed that Si reduced sensitivity to intergranular fracture or quench embrittlement, a major cause of bending fatigue crack initiation, and contributed to variable fatigue performance, with both low-cycle failures and runout performance at applied stresses significantly above measured endurance limits.

The development of new catalytic materials is still dominated by trial and error methods, even though the experimental and theoretical bases for their characterization have improved dramatically in recent years. Although it has been successful, the empirical development of catalytic materials is time consuming and expensive with no guarantee of success. We have been exploring computationally complex but experimentally simple systems to establish a “catalysis by design” protocol that combines the power of theory and experiment. We hope to translate the fundamental insights directly into a complete catalyst system that is technologically relevant. The essential component of this approach is that the catalysts are iteratively examined by both theoretical and experimental methods.

The heat treatment of steel parts is an essential step in the manufacturing of high-performance components for a variety of commercial and military products. Distortion in the size and shape of parts resulting from the heat treatment process is a pervasive manufacturing problem that causes higher finishing costs, excessive scrap and rework, long delivery times, and negative environmental impact. To date, techniques that have been developed to reduce or eliminate heat treatment distortion are largely based on experience and have been limited to trial and error. This presentation describes the philosophy and results of an ongoing collaborative project to develop a methodology and computer simulation capability to predict ferrous alloy component response (distortion, residual stress, and microstructure) to industrial heat treatment processes for automotive, truck, bearing, and aerospace applications.