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This study was designed to investigate how the spectral power distribution (SPD) of LED headlamps (including correlated color temperature, CCT) affects both objective driving performance and subjective responses of drivers. The results of this study are not intended to be the only considerations used in choosing SPD, but rather to be used along with results on how SPD affects other considerations, including visibility and glare. Twenty-five subjects each drove 5 different headlamps on each of 5 experimental vehicles. Subjects included both males and females, in older (64 to 85) and younger (20 to 32) groups. The 5 headlamps included current tungsten-halogen (TH) and high-intensity discharge (HID) lamps, along with three experimental LED lamps, with CCTs of approximately 4500, 5500, and 6500 K. Driving was done at night on public roads, over a 21.5-km route that was selected to include a variety of road types.

An experimental investigation of non-intrusive combustion sensing was performed using a tri-axial accelerometer mounted to the engine block of a small-bore high-speed 4-cylinder compression-ignition direct-injection (CIDI) engine. This study investigates potential techniques to extract combustion features from accelerometer signals to be used for cycle-to-cycle engine control. Selection of accelerometer location and vibration axis were performed by analyzing vibration signals for three different locations along the block for all three of the accelerometer axes. A magnitude squared coherence (MSC) statistical analysis was used to select the best location and axis. Based on previous work from the literature, the vibration signal filtering was optimized, and the filtered vibration signals were analyzed. It was found that the vibration signals correlate well with the second derivative of pressure during the initial stages of combustion.

With ongoing concerns about the elevated levels of ambient air pollution in urban areas and the contribution from heavy-duty diesel vehicles, hybrid electric vehicles are considered as a potential solution as they are perceived to be more fuel efficient and less polluting than their conventional engine counterparts. However, recent studies have shown that real-world emissions may be substantially higher than those measured in the laboratory, mainly due to operating conditions that are not fully accounted for in dynamometer test cycles. At the U.S. EPA National Fuel and Vehicle Emissions Laboratory (NVFEL) the in-use criteria emissions and energy efficiency of heavy-duty class 8 vehicles (up to 36280 kg) can be evaluated under controlled conditions in the heavy-duty chassis dynamometer test.

This paper addresses scheduling of quantized power levels (including part load operation and startup/shutdown periods) for a propane powered solid oxide fuel cell (SOFC) hybridized with a lithium-ion battery for a tracked mobile robot. The military requires silent operation and long duration missions, which cannot be met by batteries alone due to low energy density or with combustion engines due to noise. To meet this need we consider an SOFC operated at a few discrete power levels where maximum system efficiency can be achieved. The fuel efficiency decreases during transients and resulting thermal gradients lead to stress and degradation of the stack; therefore switching power levels should be minimized. Excess generated energy is used to charge the battery, but when it’s fully charged the SOFC should be turned off to conserve fuel.

Design of military vehicle needs to meet often conflicting requirements such as high mobility, excellent fuel efficiency and survivability, with acceptable cost. In order to reduce the development cost, time and associated risk, as many of the design questions as possible need to be addressed with advanced simulation tools. This paper describes a methodology to design a fuel efficient powerpack unit for a series hybrid electric military vehicle, with emphasis on the e-machine design. The proposed methodology builds on previously published Finite element based analysis to capture basic design features of the generator with three variables, and couples it with a model reduction technique to rapidly re-design the generator with desired fidelity. The generator is mated to an off the shelf engine to form a powerpack, which is subsequently evaluated over a representative military drive cycles.

Plenoptic particle tracking velocimetry (PTV) shows great potential for three-dimensional, three-component (3D3C) flow measurement with a simple single-camera setup. It is therefore especially promising for applications in systems with limited optical access, such as internal combustion engines. The 3D visualization of a plenoptic imaging system is achieved by inserting a micro-lens array directly anterior to the camera sensor. The depth is calculated from reconstruction of the resulting multi-angle view sub-images. With the present study, we demonstrate the application of a plenoptic system for 3D3C PTV measurement of engine-like air flow in a steady-state engine flow bench. This system consists of a plenoptic camera and a dual-cavity pulsed laser. The accuracy of the plenoptic PTV system was assessed using a dot target moved by a known displacement between two PTV frames.

This study uses full drive cycle simulation to compare the fuel consumption of a vehicle with a turbocharged (TC) engine to the same vehicle with an alternative boosting technology, namely, a hybrid supercharger, in which a planetary gear mechanism governs the power split to the supercharger between the crankshaft and a 48 V 5 kW electric motor. Conventional mechanically driven superchargers or electric superchargers have been proposed to improve the dynamic response of boosted engines, but their projected fuel efficiency benefit depends heavily on the engine transient response and driver/cycle aggressiveness. The fuel consumption benefits depend on the closed-loop engine responsiveness, the control tuning, and the torque reserve needed for each technology. To perform drive cycle analyses, a control strategy is designed that minimizes the boost reserve and employs high rates of combustion dilution via exhaust gas recirculation (EGR).

This paper describes a novel design and verification process for analytical methods used in the development of advanced combustion strategies in internal combustion engines (ICE). The objective was to improve brake thermal efficiency (BTE) as part of the US Department of Energy SuperTruck program. The tools and methods herein discussed consider spray formation and injection schedule along with piston bowl design to optimize combustion efficiency, air utilization, heat transfer, emission, and BTE. The methodology uses a suite of tools to optimize engine performance, including 1D engine simulation, high-fidelity CFD, and lab-scale fluid mechanic experiments. First, a wide range of engine operating conditions are analyzed using 1-D engine simulations in GT Power to thoroughly define a baseline for the chosen advanced engine concept; secondly, an optimization and down-select step is completed where further improvements in engine geometries and spray configurations are considered.

Connected vehicles (CVs) have situational awareness that can be exploited for control and optimization of the powertrain system. While extensive studies have been carried out for energy efficiency improvement of CVs via eco-driving and planning, the implication of such technologies on the thermal responses of CVs (including those of the engine and aftertreatment systems) has not been fully investigated. One of the key challenges in leveraging connectivity for optimization-based thermal management of CVs is the relatively slow thermal dynamics, which necessitate the use of a long prediction horizon to achieve the best performance. Long-term prediction of the CV speed, unlike the short-range prediction based on vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communications-based information, is difficult and error-prone.

The article solves the problem of reducing electric power losses of the traction induction machine rotor to prevent its overheating in nominal and high-load modes. Electric losses of the rotor power are optimized by the stabilization of the main magnetic flow of the electric machine at a nominal level with the amplitude-frequency control in a wide range of speeds and increased loads. The quasi-independent excitation of the induction machine allows us to increase the rigidity of mechanical characteristics, decrease the rotor slip at nominal loads and overloads and significantly decrease electrical losses in the rotor as compared to other control methods. The article considers the technology of converting the power of individual phases into a single energy flow using a three-phase electric machine equivalent circuit and obtaining an energy model in the form of equations of instantaneous active and reactive power balance.

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).

This simulation study explores the potential synergy between the HCCI engine system and three hybrid electric vehicle (HEV) configurations, and proposes the supervisory control strategy that maximizes the benefits of combining these two technologies. HCCI operation significantly improves fuel efficiency at part load, while hybridization aims to reduce low load/low speed operation. Therefore, a key question arises: are the effects of these two technologies additive or overlapping? The HEV configurations include two parallel hybrids with varying degrees of electrification, e.g. with a 5kW integrated starter/motor (“Mild”) and with a 10 kW electric machine (“Medium”), and a power-split hybrid. The engine is a dual-mode, SI-HCCI system and the engine map reflects the impact of HCCI on brake specific fuel consumption.

The front rail, as one main energy absorption component of vehicle front structures, should present steady progressive collapse along its axis and avoid bending collapse during the front oblique impact, but when the angle of loading direction is larger than some critical angle, it will appear bending collapse causing reduced capability of crash energy absorption. This paper is concerned with crashworthiness design of the front rail on a vehicle chassis frame structure considering uncertain crash directions. The objective is to improve the crash direction adaptability of the front rail, without deteriorating the vehicle's crashworthiness performance. Magic Cube (MQ) approach, a systematic design approach, is conducted to analyze the design problem. By applying Space Decomposition of MQ, an equivalent model of the vehicle chassis frame is generated, which simplifies the design problem.

Homogenous Charge Compression Ignition (HCCI) engines offer a good potential for achieving high fuel efficiency while virtually eliminating NOx and soot emissions from the exhaust. However, realizing the full fuel economy potential at the vehicle level depends on the size of the HCCI operating range. The usable HCCI range is determined by the knock limit on the upper end and the misfire limit at the lower end. Previously proven high sensitivity of the HCCI process to thermal conditions leads to a hypothesis that combustion chamber deposits (CCD) could directly affect HCCI combustion, and that insight about this effect can be helpful in expanding the low-load limit. A combustion chamber conditioning process was carried out in a single-cylinder gasoline-fueled engine with exhaust re-breathing to study CCD formation rates and their effect on combustion. Burn rates accelerated significantly over the forty hours of running under typical HCCI operating conditions.

A single-cylinder Direct Injection Spark Ignition (DISI) engine with optical access was used to investigate the effects of ethanol/gasoline blends on in-cylinder formation of particulate matter (PM) and fuel spray characteristics. Indolene was used as a baseline fuel and two blends of 50% and 85% ethanol (by volume, balance indolene) were investigated. Time resolved thermal radiation (incandescence/natural luminosity) of soot particles and fuel spray characteristics were recorded using a high speed camera. The images were analyzed to quantify soot formation in units of relative image intensity as a function of important engine operating conditions, including ethanol concentration in the fuel, fuel injection timing (250, 300 and 320° bTDC), and coolant temperature (25°C and 90°C). Spatially-integrated incandescence was used as a metric to quantify the level of in-cylinder PM formed at the different operating conditions.

A detailed chemical kinetic mechanism, consisting of 22 species and 104 elementary reactions, has been used in conjunction with the multi-dimensional reactive flow code KIVA-3 to study autoignition of natural gas injected under compression ignition conditions. Calculations for three different blends of natural gas are performed on a three-dimensional computational grid by modeling both the injection and ignition processes. Ignition delay predictions at pressures and temperatures typical of top-dead-center conditions in compression ignition engines compare well with the measurements of Naber et al. [1] in a combustion bomb. Two different criteria, based on pressure rise and mass of fuel burned, are used to detect the onset of ignition. Parametric studies are conducted to show the effect of additives like ethane and hydrogen peroxide in increasing the fuel consumption rate.

Meeting diesel engine emission standards for heavy-duty vehicles can be achieved by simultaneous injection of fuel and water. An injection system for instantaneous mixing of fuel and water in the combustion chamber has been developed by injecting water in a mixing passage located in the periphery of the fuel spray. The fuel spray is then entrained by water and hot air before it burns. The experimental work was carried out on a Rapid Compression Machine and on a Komatsu direct-injection heavy-duty diesel engine with a high pressure common rail fuel injection system. It was also supported by Computational Fluid Dynamics simulations of the injection and combustion processes in order to evaluate the effect of water vapor distribution on cylinder temperature and NOX formation. It has been concluded that when the water injection is appropriately timed, the combustion speed is slower and the cylinder temperature lower than in conventional diesel combustion.

The Energy Finite Element Analysis (EFEA) has been developed for evaluating the vibro-acoustic behavior of complex systems. In the past EFEA results have been compared successfully to measured data for Naval, automotive, and aircraft systems. The main objective of this paper is to present information about the process of developing EFEA models for two configurations of a business jet, performing analysis for computing the vibration and the interior noise induced from exterior turbulent boundary layer excitation, and discussing the correlation between test data and simulation results. The structural EFEA model is generated from an existing finite element model used for stress analysis during the aircraft design process. Structural elements used in the finite element model for representing the complete complex aircraft structure become part of the EFEA structural model.

Federal standards that mandate improved fuel economy have resulted in the increased use of lightweight materials in automotive applications. However, the environmental burdens associated with a product extend well beyond the use phase. Life cycle assessment is the science of determining the environmental burdens associated with the entire life cycle of a given product from cradle-to-grave. This report documents the environmental burdens associated with every phase of the life cycle of two fuel tanks utilized in full-sized 1996 GM vans. These vans are manufactured in two configurations, one which utilizes a steel fuel tank, and the other a multi-layered plastic fuel tank consisting primarily of high density polyethylene (HDPE). This study was a collaborative effort between GM and the University of Michigan's National Pollution Prevention Center, which received funding from EPA's National Risk Management Research Laboratory.

At the forefront of intelligent vehicle technologies are vehicle-to-vehicle communication (V2V) and vehicle-infrastructure integration (VII). Their capabilities can be added to currently-available systems, such as adaptive cruise control (ACC), to drastically decrease the number and severity of collisions, to ease traffic flow, and to consequently improve fuel efficiency and environmental friendliness. There has been extensive government, industry, and academic involvement in developing these technologies. This paper explores the capabilities and challenges of vehicle-based technology and examines ways that policymakers can foster implementation at the federal, state, and local levels.