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Ethanol fuel has received renewed attention in recent years because of its oxygenate content and its potential to reduce greenhouse gas emissions from spark ignition engines. The economic impact on farm industry has been one of the drivers for its use in engines in the U.S. Although ethanol, in various blends, has been used in automotive engines for almost a decade the fuel has seldom been utilized in off-highway engines where the fuel systems are not well controlled. This investigation was conducted to evaluate exhaust emissions and combustion characteristics of E85 fuel in an off-highway engine used in farm equipment. A single-cylinder, four-stroke, spark ignition engine equipped with a carburetor was used to investigate combustion and exhaust emissions produced by gasoline and blends of gasoline and ethanol fuels. The engine fuel system was modified to handle flow rates required by the engine. A variable size-metering orifice was used to control air-to-fuel ratios.

Developing a new technology requires decision-makers to understand the technology's implications on an organization's objectives, which depend on user needs targeted by the technology. If these needs are common between two organizations, collaboration could result in more efficient technology development. For hybrid truck design, both commercial manufacturers and the military have similar performance needs. As the new technology penetrates the truck market, the commercial enterprise must quantify how the hybrid's superior fuel efficiency will impact consumer purchasing and, thus, future enterprise profits. The Army is also interested in hybrid technology as it continues its transformation to a more fuel-efficient force. Despite having different objectives, maximizing profit and battlefield performance, respectively, the commercial enterprise and Army can take advantage of their mutual needs.

The fidelity of the hybrid electric vehicle simulation is increased with the integration of a computationally-efficient finite-element based electric machine model, in order to address optimization of component design for system level goals. In-wheel electric motors are considered because of the off-road military application which differs significantly from commercial HEV applications. Optimization framework is setup by coupling the vehicle simulation to the constrained optimization solver. Utilizing the increased design flexibility afforded by the model, the solver is able to reshape the electric machine's efficiency map to better match the vehicle operation points. As the result, the favorable design of the e-machine is selected to improve vehicle fuel economy and reduce cost, while satisfying performance constraints.

The components in a hybrid electric vehicle (HEV) powertrain include the battery pack, an internal combustion engine, and the electric machines such as motors and possibly a generator. These components generate a considerable amount of heat during driving cycles. A robust thermal management system with advanced controller, designed for temperature tracking, is required for vehicle safety and energy efficiency. In this study, a hybridized mid-size truck for military application is investigated. The paper examines the integration of advanced control algorithms to the cooling system featuring an electric-mechanical compressor, coolant pump and radiator fans. Mathematical models are developed to numerically describe the thermal behavior of these powertrain elements. A series of controllers are designed to effectively manage the battery pack, electric motors, and the internal combustion engine temperatures.

The paper describes a new hybrid vehicle design option having very low energy storage capability, and in particular, a parallel hybrid with hydraulic storage and reapplication of braking energy. The operating efficiency of the propulsion system at light loads is substantially improved by splitting the engine into two segments, and finding ways of shutting down one or both engine segments whenever possible. The hybrid vehicle utilizes primarily current technologies. A diesel powered parallel hybrid as described demonstrates a reduction in fuel consumption of 53.9% on a volume basis when compared with an equivalent baseline vehicle.

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.

This paper describes a computerized value analysis tool (VAT) developed to aid automotive interior designers, engineers and planners to achieve the high levels of perceived quality of materials used in automotive door trim panels. The model requires a number of inputs related to types of materials, their manufacturing processes and customer perceived quality ratings, costs and importance of materials, features located in different areas of the door trim panel, etc. It allows the user to conduct iterative evaluation of total cost, total weighted customer perceived quality ratings, and estimates of perceived value (perceived quality divided by cost) for different door trim areas as well as the entire door trim panel. The VAT, thus, allows value and cost management related to materials and processing choices for automotive interiors.

Controller Area Network (CAN), the de facto standard for in-vehicle networks, has insufficient security features and thus is inherently vulnerable to various attacks. To protect CAN bus from attacks, intrusion detection systems (IDSs) based on advanced deep learning methods, such as Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN), have been proposed to detect intrusions. However, those models generally introduce high latency, require considerable memory space, and often result in high energy consumption. To accelerate intrusion detection and also reduce memory requests, we exploit the use of Binarized Neural Network (BNN) and hardware-based acceleration for intrusion detection in in-vehicle networks. As BNN uses binary values for activations and weights rather than full precision values, it usually results in faster computation, smaller memory cost, and lower energy consumption than full precision models.

A GT-suite commercial code was used to develop a fully integrated model of a light duty commercial vehicle with a V6 diesel engine, to study the use of a BorgWarner dual mode coolant pump (DMCP) in active thermal management of the vehicle. An Urban Dynamometer Driving Schedule (UDDS) was used to validate the simulation results with the experimental data. The conventional mechanical pump from the validated model was then replaced with the dual mode coolant pump. The control algorithm for the pump was based on controlling the coolant temperature with pump speed. Maximum electrical speed of the pump and the efficiency of the pump were used to determine whether the pump should run in mechanical or electrical mode. The model with the dual mode coolant pump was simulated for the UDDS cycle to demonstrate the effectiveness of control strategy.

This paper summarizes the results of Phase 1, Concept Definition, of the AATD program and identifies the reasons such a new test device is needed. The following areas are addressed: 1) injury priority from accident data; 2) current dummy design, use, and potential improvements; and 3) technical characteristics and design concepts for a new AATD, its data processing, and its certification systems.

A computational methodology has been developed for loss prediction in intake regions of internal combustion engines. The methodology consists of a hierarchy of four major tasks: (1) proper computational modeling of flow physics; (2) exact geometry and high quality and generation; (3) discretization schemes for low numerical viscosity; and (4) higher order turbulence modeling. Only when these four tasks are dealt with properly will a computational simulation yield consistently accurate results. This methodology, which is has been successfully tested and validated against benchmark quality data for a wide variety of complex 2-D and 3-D laminar and turbulent flow situations, is applied here to a loss prediction problem from industry. Total pressure losses in the intake region (inlet duct, manifold, plenum, ports, valves, and cylinder) of a Caterpillar diesel engine are predicted computationally and compared to experimental data.

The Honda Particulate Matter Index (PMI) is a very helpful tool which provides an indication of a fuel’s sooting tendency. Currently, the index is being used by various laboratories and vehicle OEMs as a metric to understand a fuels impact on automotive engine sooting, in preparation for new global emissions regulations. The calculation of the index involves generating detailed hydrocarbon analysis (hydrocarbon molecular speciation) using gas chromatography laboratory equipment and the PMI calculation requires the exact list of compounds and correct naming conventions to work properly. The analytical methodology can be cumbersome, when the gas chromatography methodology has to be adjusted for new compounds that are not in the method, or if the compounds are not matching the list for quantification. Also, the method itself is relatively expensive, and not easily transferrable between labs.

The addition of synthetic traffic to a driving simulation greatly enhances the realism of the virtual world. Giving this traffic human-like behavior is likewise desirable, and has been the focus of some research over the past few years. This paper presents a modular architecture for including autonomous traffic in a driving simulation, and describes the first steps taken toward the application of this architecture to the DaimlerChrysler Auburn Hills Simulator. By separating the planning part of the agent from the low-level control and vehicle dynamics systems, the described architecture permits the inclusion of powerful, previously developed components in a straightforward way; in the present application, agents use Soar to reason about their actions. This paper gives an overview of the structures of the agents, and of the entire system, describes the components and their implementations, and discusses the current state of the project and plans for the future.

This study is to explore the application of electrorheology (ER) to the real-time control of damping forces that are transmitted through the nose landing gear for an F-106B aircraft. The main part of the landing gear is a strut that consists of a pneumatic spring and an ER controlled damper that is situated on the strut centerline and applies a force directly opposing the vertical displacement of the nose wheel. The damping element rotates in response to strut displacement, employing a co-axial arrangement of stator and rotor plates connected to the opposing electrodes in the control circuit. The vertical displacement is converted into rotation of the damper through a screw-nut mechanism. The ER fluid between the electrodes is thus engaged in shear along circumferential lines of action. This design results in a fast time response and a high ratio of strut forces achieved under ER- vs. zero-field control. Compact size and simplicity in fabrication are also attained.

The recent advent of highly effective drilling and extraction technologies has decreased the price of natural gas and renewed interest in its use for transportation. Of particular interest is the conversion of dedicated diesel engines to operate on dual-fuel with natural gas injected into the intake manifold. Dual-fuel systems with natural gas injected into the intake manifold replace a significant portion of diesel fuel energy with natural gas (generally 50% or more by energy content), and produce lower operating costs than diesel-only operation. Diesel-natural gas engines have a high compression ratio and a homogeneous mixture of natural gas and air in the cylinder end gases. These conditions are very favorable for knock at high loads. In the present study, knock prediction concepts that utilize a single step Arrhenius function for diesel-natural gas dual-fuel engines are evaluated.

Stringent fuel economy and emissions regulations have driven development of new mixture preparation technologies and increased spark-ignition engine complexity. Additional degrees of freedom, brought about by devices such as cam phasers and charge motion control valves, enable greater range and flexibility in engine control. This permits significant gains in fuel efficiency and emission control, but creates challenges related to proper engine control and calibration techniques. Accurate experimental characterization of high degree of freedom engines is essential for addressing the controls challenge. In particular, this paper focuses on the evaluation of three experimental residual gas fraction measurement techniques for use in a spark ignition engine equipped with dual-independent variable camshaft phasing (VVT).

Simultaneous measurements of the radial and the tangential components of velocity are obtained in a high-speed, direct-injection diesel engine typical of automotive applications. Results are presented for engine operation with fuel injection, but without combustion, for three different swirl ratios and four injection pressures. With the mean and fluctuating velocities, the r-θ plane shear stress and the mean flow gradients are obtained. Longitudinal and transverse length scales are also estimated via Taylor's hypothesis. The flow is shown to be sufficiently homogeneous and stationary to obtain meaningful length scale estimates. Concurrently, the flow and injection processes are simulated with KIVA-3V employing a RNG k-ε turbulence model. The measured turbulent kinetic energy k, r-θ plane mean strain rates ( 〈Srθ〉, 〈Srr〉, and 〈Sθθ〉 ), deviatoric turbulent stresses , and the r-θ plane turbulence production terms are compared directly to the simulated results.

When unexpected integrated lubricant-related problems occur, for example, high-speed operating conditions, lubricants can be degraded and even fail to reach certain automatic transmission parts. Dryout of oil films means a serious lack of lubrication, which may damage the power transmission line and key parts. Dryout of ATF is analogous to that in forced convective boiling and condensation. It thus requires special efforts to determine the mechanics that induce such fluid transport phenomena. This paper presents an experimental investigation of lubricant activities in the main shaft. Dimensional analysis is applied, and flow maps of the air-oil flow and dryout regimes are constructed. Correlations closely agree with the data and reveal the possibility of dryout. Heat transfer effect is briefly discussed.

A series of inflator tank tests was carried out to determine the amount of transient heat losses to the tank wall during these tests. The time history data of tank wall temperature, and tank interior gas temperature and pressure, were measured. The tank wall temperature data were analyzed using an inverse heat conduction method to generate the transient heat loss fluxes from the tank gas to the tank wall. The validity of the results are discussed along with the physical reasoning and experimental observations. This is the first part of an effort in a research project to develop a comprehensive heat transfer model to predict the transient heat losses to the tank wall during the inflator tank test.

After-injection is the introduction of additional fuel to the combustion chamber after the end of the main injection. It is a persistent diesel fuel injection problem which usually results in reduced engine power and economy and increased emissions. After-injection is caused by uncontrolled pressure transients at the injector after the opening of the pump spill port. These pressure transients are related to the wave propagation phenomena in the high-pressure pipeline connecting the pump and injector. Use of experimental trial-and-error methods in attempts to control this phenomenon has met with limited success. The analytical control method described in another paper is used to determine design means by which after-injection may be controlled. Further investigation and evaluation of two design changes which release the injection system excess elastic energy in a controlled manner are considered herein. One design change is the addition of a control valve in the pump delivery chamber.