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An experimental study is performed for homogeneous charge compression ignition (HCCI) combustion focusing on late phasing conditions with high cyclic variability (CV) approaching misfire. High CV limits the feasible operating range and the objective is to understand and quantify the dominating effects of the CV in order to enable controls for widening the operating range of HCCI. A combustion analysis method is developed for explaining the dynamic coupling in sequences of combustion cycles where important variables are residual gas temperature, combustion efficiency, heat release during re-compression, and unburned fuel mass. The results show that the unburned fuel mass carries over to the re-compression and to the next cycle creating a coupling between cycles, in addition to the well known temperature coupling, that is essential for understanding and predicting the HCCI behavior at lean conditions with high CV.

The role of automotive electronics in light duty vehicles is continuing to expand rapidly. In this paper an overview of a 1986 Delphi forecast of major trends is presented. Trends discussed include electronics as a fraction of vehicle and component cost and projections of basic vehicle features supported by electronic technology. In addition, basic trends in diagnostics and multiplexing are presented. Several issues in support of automotive electronics are discussed, including the systems approach to vehicle engineering, the importance of developing a proper market strategy, and the continued major role of energy economics. The Delphi forecasting technique and its governing concepts are reviewed as a method to predict the future of automotive technology.

The global energy situation, the dependence of the transportation sector on fossil fuels, and a need for rapid response to the global warming challenge, provide a strong impetus for development of fuel efficient vehicle propulsion. The task is particularly challenging in the case of trucks due to severe weight/size constraints. Hybridization is the only approach offering significant breakthroughs in near and mid-term. In particular, the series configuration decouples the engine from the wheels and allows full flexibility in controlling the engine operation, while the hydraulic energy conversion and storage provides exceptional power density and efficiency. The challenge stems from a relatively low energy density of the hydraulic accumulator, and this provides part of the motivation for a simulation-based approach to development of the system power management. The vehicle is based on the HMMWV platform, a 4×4 off-road truck weighing 5112 kg.

In order to develop confidence in numerical models which are used for automotive crash simulations, results are compared with test data. Modeling assumptions are made when constructing a simulation model for a complex system, such as a vehicle. Through a thorough understanding of the modeling assumptions an appropriate set of variables can be selected and adjusted in order to improve correlation with test data. Such a process can lead to better modeling practices when constructing a simulation model. Comparisons between the time history of acceleration responses from test and simulations are the most challenging. Computing accelerations correctly is more difficult compared to computing displacements, velocities, or intrusion levels due to the second order differentiation with time. In this paper a methodology for enabling the update of a simulation model for improved correlation is presented.

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.

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.

The Energy Finite Element Analysis(EFEA) is a recent development for high frequency vibro-acoustic analysis, and constitutes an evolution in the area of high frequency computations. The EFEA is a wave based approach, while the SEA is a modal based approach. In this paper the similarities in the theoretical development of the two methods are outlined. The main scope of this paper is to establish the validity of the EFEA by analyzing several complex structural-acoustic systems. The EFEA solutions are compared successfully to SEA results and to solutions obtained from extremely dense conventional FEA models.

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.

This paper assesses the technical potential, costs and benefits of improving the fuel economy of light-duty trucks over the next five to ten years in the United States using conventional technologies. We offer an in-depth analysis of several technology packages based on a detailed vehicle system modeling approach. Results are provided for fuel economy, cost, oil savings and reductions in greenhouse gas emissions. We examine a range of refinements to body, powertrain and electrical systems, reflecting current best practice and emerging technologies such as lightweight materials, high-efficiency IC engines, integrated starter-generator, 42 volt electrical system and advanced transmission. In this paper, multiple technological pathways are identified to significantly improve fleet average light-duty-truck fuel economy to 27.0 MPG or higher with net savings to consumers.

In-cylinder fluid velocity is measured in an optically accessible, fired HSDI engine at idle. The velocity field is also calculated, including the full induction stroke, using multi-dimensional fluid dynamics and combustion simulation models. A detailed comparison between the measured and calculated velocities is performed to validate the computed results and to gain a physical understanding of the flow evolution. Motored measurements are also presented, to clarify the effects of the fuel injection process and combustion on the velocity field evolution. The calculated mean in-cylinder angular momentum (swirl ratio) and mean flow structures prior to injection agree well with the measurements. Modification of the mean flow by fuel injection and combustion is also well captured.

The results of an experimental investigation of the flow over a pickup truck are presented. The main objectives of the study are to gain a better understanding of the flow structure in near wake region, and to obtain a detailed quantitative data set for validation of numerical simulations of this flow. Experiments were conducted at moderate Reynolds numbers (∼3×105) in the open return tunnel at the University of Michigan. Measured quantities include: the mean pressure on the symmetry plane, unsteady pressure in the bed, and Particle Image Velocimetry (PIV) measurements of the flow in the near wake. The unsteady pressure results show that pressure fluctuations in the forward section of the bed are small and increase significantly at the edge of the tailgate. Pressure fluctuation spectra at the edge of the tailgate show a spectral peak at a Strouhal number of 0.07 and large energy content at very low frequency.

Automotive seats are commonly described by one-dimensional measurements, including those documented in SAE J2732. However, 1-D measurements provide minimal information on seat shape. The goal of this work was to develop a statistical framework to analyze and model the surface shapes of seats by using techniques similar to those that have been used for modeling human body shapes. The 3-D contour of twelve driver seats of a pickup truck and sedans were scanned and aligned, and 408 landmarks were identified using a semi-automatic process. A template mesh of 18,306 vertices was morphed to match the scan at the landmark positions, and the remaining nodes were automatically adjusted to match the scanned surface. A principal component (PC) analysis was performed on the resulting homologous meshes. Each seat was uniquely represented by a set of PC scores; 10 PC scores explained 95% of the total variance. This new shape description has many applications.

Automated clutches for vehicle startup is being increasingly deployed in commercial trucks for benefits, which include driver comfort, gradient performance, improved clutch life, emissions and driveline vibration reduction potential. The process of designing the controller is divided into 2 parts. Firstly, the parameter estimation of previously developed driveline models is carried out. The procedure involves an off-line minimization technique based on measured and estimated speeds. Secondly, the nominal plant model is used to develop LQR based optimal control strategy, which takes into account the slip time, dissipated power and slip acceleration. Mathematical expression of the performance index is clearly developed. A variety of clutch lock up profiles can be incorporated by changing a single tuning parameter, thus providing the driver the ability to select a launch profile based on specific driving objectives.

This paper presents a simple method of using Voronoi partitions for estimating vehicle fuel economy from a limited set of engine operating conditions. While one of the overarching goals of engine research is to continually improve vehicle fuel economy, evaluating the impact of a change in engine operating efficiency on the resulting fuel economy is a non-trivial task and typically requires drive cycle simulations with experimental data or engine model predictions and a full suite of engine controllers over a wide range of engine speeds and loads. To avoid the cost of collecting such extensive data, proprietary methods exist to estimate fuel economy from a limited set of engine operating conditions. This study demonstrates the use of Voronoi partitions to cluster and quantize the fuel consumed along a complex trajectory in speed and load to generate fuel consumption estimates based on limited simulation or experimental results.

Existing methods for design optimization under uncertainty assume that a high level of information is available, typically in the form of data. In reality, however, insufficient data prevents correct inference of probability distributions, membership functions, or interval ranges. In this article we use an engine design example to show that optimal design decisions and reliability estimations depend strongly on uncertainty characterization. We contrast the reliability-based optimal designs to the ones obtained using worst-case optimization, and ask the question of how to obtain non-conservative designs with incomplete uncertainty information. We propose an answer to this question through the use of Bayesian statistics. We estimate the truck's engine reliability based only on available samples, and demonstrate that the accuracy of our estimates increases as more samples become available.

A primary goal of large eddy simulation, LES, is to capture in-cylinder cycle-to-cycle variability, CCV. This is a first step to assess the efficacy of 35 consecutive computed motored cycles to capture the kinetic energy in the TCC-III engine. This includes both the intra-cycle production and dissipation as well as the kinetic energy CCV. The approach is to sample and compare the simulated three-dimensional velocity equivalently to the available two-component two-dimensional PIV velocity measurements. The volume-averaged scale-resolved kinetic energy from the LES is sampled in three slabs, which are volumes equal to the two axial and one azimuthal PIV fields-of-view and laser sheet thickness. Prior to the comparison, the effects of sampling a cutting plane versus a slab and slabs of different thicknesses are assessed. The effects of sampling only two components and three discrete planar regions is assessed.

A comprehensive model for sprays emerging from high-pressure swirl injectors in DISI engines has been developed accounting for both primary and secondary atomization. The model considers the transient behavior of the pre-spray and the steady-state behavior of the main spray. The pre-spray modeling is based on an empirical solid cone approach with varying cone angle. The main spray modeling is based on the Liquid Instability Sheet Atomization (LISA) approach, which is extended here to include the effects of swirl. Mie Scattering, LIF, PIV and Laser Droplet Size Analyzer techniques have been used to produce a set of experimental data for model validation. Both qualitative comparisons of the evolution of the spray structure, as well as quantitative comparisons of spray tip penetration and droplet sizes have been made. It is concluded that the model compares favorably with data under atmospheric conditions.

The influence of the bulk in-cylinder flow on the spray evolution, evaporation, fuel-air mixing and subsequent flame propagation has been studied in an optical SIDI engine. Quantitative LIF imaging of equivalence ratios was used to characterize the mixture formation and the influence of the local equivalence ratio at the time of spark on the flame propagation. Two extreme bulk flow conditions - high and low swirl - were investigated and pronounced differences in mixture homogeneity and flame propagation were found and characterized.

Using the CDC (SAE J224), a comparison of the NASS data and the UMTRI field accident files (UM series) indicates a similar distribution of offset frontal crashes. Offset frontal damage occurs in 56-61% of crashes, often involving more than one third of the front of the car. Lap-shoulder belted drivers sustain more AIS 2 or greater injuries when there is interior intrusion and occur more often when the offset damage is in front of the driver. However, this may well be due to the severity of the crash. European studies have no uniformity as to offset frontal collision descriptors are difficult to interpret, or to compare one to another.

Since muscles act to translate an electrical impulse from the central nervous system into motion, it is essential to have a suitable mathematical model for muscles and groups of muscles for a virtual soldier environment. This paper presents a methodology in which the muscle contraction is broken down into three distinct physiological processes: calcium release and re-absorption by the sarcoplasmic reticulum, the rate at which calcium binds and unbinds to troponin, and the generation of force due to cross-bridge cycling and the elasticity of the muscle fibers. These processes have been successfully modeled by Ding and Wexler as a system of coupled differential and algebraic equations. These equations give the calcium-time history and the force time history of the muscle. By varying the electrical stimulation rates, the muscles can produce forces of varying magnitude and duration over which the force can be maintained.