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In sheet metal forming, metal flow into the die is determined by the restraint imposed by both the blankholder force and the drawbead penetration. This paper describes an experimental investigation in which both advanced binder force and drawbead technologies are used to study their effect on draw depth in the drawing of an AA6111-T4 generic non-symmetric panel. Multipoint binder loading using individual pin force adjustment applied to especially designed binder structures as well as the use of variable blankholder force were investigated in one laboratory in Germany. In another laboratory in the USA, active drawbeads were applied to the drawing of the generic panel. The results of both approaches, which are shown to be successful, are presented and discussed.

A study of particle size distributions was conducted on a Cummins M11 1995 engine using the Scanning Mobility Particle Sizer (SMPS) instrument in the baseline and downstream of the Catalyzed Particulate Filter (CPF). Measurements were made in the dilution tunnel to investigate the effect of primary dilution ratio and mixture temperature on the nuclei and accumulation mode particle formation. Experiments were conducted at two different engine modes namely Mode 11 (25% load - 311 Nm, 1800 rpm) and Mode 9 (75% load - 932 Nm, 1800 rpm). The nanoparticle formation decreased with increasing dilution ratios for a constant mixture temperature in the baseline as well as downstream of the CPF II for Mode 11 condition. At Mode 9 condition in the baseline, the dilution ratio had a little effect on the nanoparticle formation, since the distribution was not bimodal and was dominated by accumulation mode particles.

In this paper, the conversion of a production SUV to a hybrid electric vehicle with a drive system utilizing a planetary power-split transmission is presented. The uniqueness of this design comes from its ability to couple the advantages of a parallel hybrid with the advantages of a series hybrid. Depending on operating conditions and recent operating history, the drive system transitions to one of several driving modes. The drive system consists of a planetary gear set coupled to an alternator, motor, and internal combustion engine. It performs the power-split operation without the need for belt drives or clutching devices. The effects on driveability, manufacturing, fuel economy, emissions, and performance are presented along with the design, selection, and implementation of all of the vehicle conversion components.

Three-dimensional diesel engine combustion simulations with single-step chemistry have been compared with two-step and three-step chemistry by means of the Laminar and Turbulent Characteristic Time Combustion model using the Star-CD program. The second reaction describes the oxidation of CO and the third reaction describes the combustion of H2. The comparisons have been performed for two heavy-duty diesel engines. The two-step chemistry was investigated for a purely kinetically controlled, for a mixing limited and for a combination of kinetically and mixing limited oxidation. For the latter case, two different descriptions of the laminar reaction rates were also tested. The best agreement with the experimental cylinder pressure has been achieved with the three-step mechanism but the differences with respect to the two-step and single-step reactions were small.

The successful implementation of a clean, quiet, four-stroke engine into an existing snowmobile chassis has been achieved. The snowmobile is easy to start, easy to drive and environmentally friendly. The following paper describes the conversion process in detail with actual engine test data. The hydrocarbon emissions of the new, four-stroke snowmobile are 98% lower than current, production, two-stroke models. The noise production of the four-stroke snowmobile was 68 dBA during an independent wide open throttle acceleration test. If the four-stroke snowmobile were to replace all current, two-stroke snowmobiles in Yellowstone National Park (YNP), the vehicles would only produce 16% of the combined automobile and snowmobile hydrocarbon emissions compared to the current 93% produced by two-stroke snowmobiles.

The National Science Foundation recently sponsored a Workshop on Environmentally Benign Manufacturing (EBM) for the Transportation Industries. The objective of the workshop was to determine future directions of research in the EBM area and to construct a roadmap for development of future research programs. While research in the fields of Design for the Environment (DfE) and Life Cycle Analysis (LCA) have focused on the product and product life cycles, an additional focus is needed to find and develop processes with less environmental impact within the manufacturing environment. This workshop explored EBM issues with respect to the enterprise, the products, the processes and the materials.

A modified version of the Laminar and Turbulent Characteristic Time combustion model and the Hiroyasu-Magnussen soot model have been implemented in the flow solver Star-CD. Combustion simulations of three DI diesel engines, utilizing the standard k-ε turbulence model and a modified version of the RNG k-ε turbulence model, have been performed and evaluated with respect to combustion performance and emissions. Adjustments of the turbulent characteristic combustion time coefficient, which were necessary to match the experimental cylinder peak pressures of the different engines, have been justified in terms of non-equilibrium turbulence considerations. The results confirm the existence of a correlation between the integral length scale and the turbulent time scale. This correlation can be used to predict the combustion time scale in different engines.

Diesel exhaust particle size distributions were measured using an Electrical Aerosol Analyzer (EAA) with both conventional (0.31 wt. pet sulfur) and low sulfur fuel (0.01 wt pet sulfur) with and without a ceramic diesel particle filter (DPF). The engine used for this study was a 1988 heavy-duty diesel engine (Cummins LTA10-300) operated at EPA steady-state modes 9 and 11. The particle size distribution results indicated the typical bi-modal distribution; however, there were clear differences in the number of particles in each mode for all conditions. For the baseline conditions with no DPF, there was more than one order of magnitude greater number of particles in the nuclei mode for the conventional fuel as compared to the low sulfur fuel, while the accumulation modes for each fuel were nearly identical.

This study was conducted to assess the effects of a low sulfur (<0.05 wt.%) fuel and an uncatalyzed ceramic particle trap on heavy-duty diesel emissions during both steady-state operation and during periods of electrically assisted trap regeneration. A Cummins LTA10-300 engine was operated at two steady-state modes with and without the trap. The exhaust trap system included a Corning EX-54 trap with an electrically assisted regeneration system. Both regulated emissions (oxides of nitrogen - NOx, total hydrocarbons - HC, and total particulate matter - TPM) and some unregulated emissions (polynuclear aromatic hydrocarbons - PAH soluble organic fraction - SOF, sulfates, vapor phase organics, and mutagenic activity) were measured during baseline, trap, and regeneration conditions. Emissions were collected with low sulfur (0.01 wt.%) fuel and compared to emissions with a conventional sulfur (0.32 wt.%) fuel. These fuels also varied in other fuel properties.

The U.S. Bureau of Mines and Michigan Technological University are collaborating to conduct laboratory evaluations of oxidation catalytic converters (OCCs) and diesel fuels to identify combinations which minimize potentially harmful emissions. The purpose is to provide technical information concerning diesel exhaust emission control to the mining industry, regulators, and vendors of fuel and emission control devices. In this study, an Engelhard PTX 10 DVC (Ultra-10)* OCC was evaluated in the exhaust stream of an indirect injection Caterpillar 3304 PCNA mining engine using a light-duty laboratory transient cycle. This cycle was selected because it causes high emissions of particle-associated organics. Results are also reported for two different fuels with similar sulfur contents (0.03-0.04 wt pct) and a cetane number of 53, but different aromatic contents (11 vs. 20 wt pct).

A numerical simulation of autoignition of gasoline-ethanol/air mixtures has been performed using the closed homogeneous reactor model in CHEMKIN® to compute the dependence of autoignition time with ethanol concentration, pressure, temperature, dilution, and equivalence ratio. A semi-detailed validated chemical kinetic model with 142 species and 672 reactions for a gasoline surrogate fuel with ethanol has been used. The pure components in the surrogate fuel consisted of n-heptane, isooctane and toluene. The ethanol volume fraction is varied between 0 to 85%, initial pressure is varied between 20 to 60 bar, initial temperature is varied between 800 to 1200K, and the dilution is varied between 0 to 32% at equivalence ratios of 0.5, 1.0 and 1.5 to represent the in-cylinder conditions of a spark-ignition engine. The ignition time is taken to be the point where the rate of change of temperature with respect to time is the largest (temperature inflection point criteria).

Spray structure has a significant effect on emissions and performance of an internal combustion engine. The main objective of this study is to investigate spray structures based on four different multiple jet impingement injectors. These four different multiple jet-to-jet impingement injectors include 1). 4-hole injector (Case 1), which has symmetric inwardly opening nozzles; 2). 5-1-hole (Case 2); 3). 6-2-hole (Case 3); and 4). 7-3-hole (Case 4) which corresponding to 1, 2, 3 numbers of adjacent holes blocked in a 5-hole, 6-hole, and 7-hole symmetrical drill pattern, respectively. All these configurations are basically 4-holes but with different post collision spray structure. Computational Fluid Dynamics (CFD) work of these sprays has been performed using an Eulerian-Lagrangian modelling approach.

Fuel cell technology is recently becoming one of the most interesting fields for the car companies to invest in. This interest is because of their high efficiency and zero environmental pollution. Polymer electrolyte membrane fuel cells (PEMFC) are the most appropriate type of fuel cells for use in vehicles due to their low performance temperature and high power density. Air and fuel mass flow rate and partial pressure, fuel cell stack temperature, relative humidity of fuel cell membrane and heat and water management are the effective parameters of fuel cell power systems. Good transient behavior is one of the important factors that affect the success of fuel cell vehicles. In order to avoid stack voltage drop during transient condition, the control system of fuel cell vehicle is required to preserve optimal temperature, membrane hydration and partial pressure of reactants across the membrane. In this paper, we developed a dynamic model for fuel cell power system.

In this paper, a mathematical model of the SCR catalytic converter is replaced with the neural network model to accelerate the optimization process. The Euro steady state calibration test data set is used to simulate the inlet properties of the SCR catalytic converter. For each chosen condition, a separate neural network is developed. In order to generate sufficient data to form a neural network for each condition, the original mathematical model was run several times at the temperature and inlet NOx concentration of each condition with a range of different ammonia concentrations. Subsequently, using MATLAB® software, the neural network model is trained and tested for each condition. Ammonia dosing optimization is performed using multi objective genetic algorithm module of MATLAB®. The optimization objectives are NOx reduction percentage and the outlet ammonia concentration of the SCR catalytic converter.

When testing dynamic structures, it is important to note that the dynamic system in question may be submerged into a fluid during operation and to properly test the structure under the same condition in order to understand the true dynamic parameters of the system. In this way, the mass and stiffness coupling to the particular fluid, for the case of this study, automatic transmission fluid, may be taken into account. This is especially important in light structures where the coupling between the fluid mass and the structural mass may be great. A structure was tested with a laser vibrometer using several impact methods in open air to determine which impact method would be most suitable for submerged testing. The structure was then submerged in transmission fluid with an accelerometer attached and subsequently tested and compared to the previous results.

This paper presents the development of a Stochastic Knock Detection (SKD) method for combustion knock detection in a spark-ignition engine using a model based design approach. The SKD set consists of a Knock Signal Simulator (KSS) as the plant model for the engine and a Knock Detection Module (KDM). The KSS as the plant model for the engine generates cycle-to-cycle accelerometer knock intensities following a stochastic approach with intensities that are generated using a Monte Carlo method from a lognormal distribution whose parameters have been predetermined from engine tests and dependent upon spark-timing, engine speed and load. The lognormal distribution has been shown to be a good approximation to the distribution of measured knock intensities over a range of engine conditions and spark-timings for multiple engines in previous studies.

Exergy or availability is the potential of a system to do work. In this paper, an innovative exergy-based control approach is presented for Internal Combustion Engines (ICEs). An exergy model is developed for a Homogeneous Charge Compression Ignition (HCCI) engine. The exergy model is based on quantification of the Second Law of Thermodynamic (SLT) and irreversibilities which are not identified in commonly used First Law of Thermodynamics (FLT) analysis. An experimental data set for 175 different ICE operating conditions is used to construct the SLT efficiency maps. Depending on the application, two different SLT efficiency maps are generated including the applications in which work is the desired output, and the applications where Combined Power and Exhaust Exergy (CPEX) is the desired output. The sources of irreversibility and exergy loss are identified for a single cylinder Ricardo HCCI engine.

Precise cycle-to-cycle control of combustion is the major challenge to reduce fuel consumption in Homogenous Charge Compression Ignition (HCCI) engines, while maintaining low emission levels. This paper outlines a framework for simultaneous control of HCCI combustion phasing and Indicated Mean Effective Pressure (IMEP) on a cycle-to-cycle basis. A dynamic control model is extended to predict behavior of HCCI engine by capturing main physical processes through an HCCI engine cycle. Performance of the model is validated by comparison with the experimental data from a single cylinder Ricardo engine. For 60 different steady state and transient HCCI conditions, the model predicts the combustion phasing and IMEP with average errors less than 1.4 CAD and 0.2 bar respectively. A two-input two-output controller is designed to control combustion phasing and IMEP by adjusting fuel equivalence ratio and blending ratio of two Primary Reference Fuels (PRFs).

Battery management system (BMS) plays a key role in the power management of hybrid electric vehicles (HEV). It measures the state of charge (SOC), state of health (SOH) of the battery, protects the battery package and extends cells' life cycles. For HEV applications, lithium-ion battery is usually selected as electric power source due to its high specific energy, high energy density, and long life cycle. However, the non-linear characteristic of a Li-ion battery, complicated electro-chemical model, and environmental factors, raises the difficulties in the real-time estimation of the SOC for a Li-ion battery. To address this challenge, a BMS for HEVs is modeled with MATLAB/Simulink. In addition, a regenerative braking control strategy is proposed to determine the magnitude of the regenerative torque based on the battery SOC.

Numerical modeling of aftertreatment systems has been proven to reduce development time as well as to facilitate understanding of the internal physical and chemical processes occurring during different operating conditions. Such a numerical model for a catalyzed diesel particulate filter (CPF) was developed in this research work which has been improved from an existing numerical model briefly described in reference. The focus of this CPF model was to predict the effect of the catalyst on the gaseous species concentrations and to develop particulate matter (PM) filtration and oxidation models for the PM cake layer and substrate wall so as to develop an overall model that accurately predicts the pressure drop and PM oxidized during passive oxidation and active regeneration. Descriptions of the governing equations and corresponding numerical methods used with relevant boundary conditions are presented.