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Transient engine operations are modeled and simulated with a 1-D code (GT Power) using heat release and emission data computed by a 3-D CFD code (Kiva3). During each iteration step of a transient engine simulation, the 1-D code utilizes the 3-D data to interpolate the values for heat release and emissions. The 3-D CFD computations were performed for the compression and combustion stroke of strategically chosen engine operating points considering engine speed, torque and excess air. The 3-D inlet conditions were obtained from the 1-D code, which utilized 3-D heat release data from the previous 1-D unsteady computations. In most cases, only two different sets of 3-D input data are needed to interpolate the transient phase between two engine operating points. This keeps the computation time at a reasonable level. The results are demonstrated on the load response of a generator which is driven by a medium-speed diesel engine.

The need for efficient space utilization has provided a framework for the design of a 248mm family of torque converters that supports a wide choice of engine and transmission combinations. The axial length of the part and its weight have been substantially reduced while the performance range has been broadened without degradation of efficiency. The new converter operates in an expanded slipping clutch mode. It significantly contributes to the performance and fuel economy improvements of related vehicles. To meet the cost target, the comprehensive lineup and the resulting complexity have required a high level of component interchangeability. During the design phase, the manufacturing core competencies were scrutinized and process redundancies eliminated, both resulting in optimization of material selection and applicable technology.

A 2-D computational model was developed to describe the flow and filtration processes, in a honeycomb structured ceramic diesel particulate trap. This model describes the steady state trap loading, as well as the transient behavior of the flow and filtration processes. The theoretical model includes the effect of a copper fuel additive on trap loading and transient operation. The convective terms were based on a 2-D analytical flow field solution derived from the conservation of mass and momentum equations. The filtration theory incorporated in the time dependent numerical code included the diffusion, inertia, and direct interception mechanisms. Based on a measured upstream particle size distribution, using the filtration theory, the downstream particle size distribution was calculated. The theoretical filtration efficiency, based on particle size distribution, agreed very well (within 1%) with experimental data for a number of different cases.

A 2-D CFD model was developed to describe the heat transfer, and reaction kinetics in a honeycomb structured ceramic diesel particulate trap. This model describes the steady state as well as the transient behavior of the flow and heat transfer during the trap regeneration processes. The trap temperature profile was determined by numerically solving the 2-D unsteady energy equation including the convective, heat conduction and viscous dissipation terms. The convective terms were based on a 2-D analytical flow field solution derived from the conservation of mass and momentum equations (Opris, 1997). The reaction kinetics were described using a discretized first order Arrhenius function. The 2-D term describing the reaction kinetics and particulate matter conservation of mass was added to the energy equation as a source term in order to represent the particulate matter oxidation. The filtration model describes the particulate matter accumulation in the trap.

In July 1997, the Pacific Northwest and Alaska Regional Bioenergy Program, in cooperation with several industrial and institutional partners initiated a long-haul 322,000 km (200,000 mile) operational demonstration using a biodiesel and diesel fuel blend in a 324 kW (435 HP), Caterpillar 3406E Engine, and a Kenworth Class 8 heavy duty truck. This project was designed to: develop definitive biodiesel performance information, collect emissions data for both regulated and non-regulated compounds including mutagenic activity, and collect heavy-duty operational engine performance and durability information. To assess long-term engine durability and wear; including injector, valve and port deposit formations; the engine was dismantled for inspection and evaluation at the conclusion of the demonstration. The fuel used was a 50% blend of biodiesel produced from used cooking oil (hydrogenated soy ethyl ester) and 50% 2-D petroleum diesel.

Evaluations of the liner pitting protection performance provided by engine coolant corrosion inhibitors and supplemental coolant additives have presented many problems. Current practice involves the use of full scale engine tests to show that engine coolant inhibitors provide sufficient liner pitting protection. These are too time-consuming and expensive to use as the basis for industry-wide specifications. Ultrasonic vibratory test rigs have been used for screening purposes in individual labs, but these have suffered from poor reproducibility and insufficient additive differentiation. A new test procedure has been developed that reduces these problems. The new procedure compares candidate formulations against a good and bad reference fluid to reduce the concern for problems with calibration and equipment variability. Cast iron test coupons with well-defined microstructure and processing requirements significantly reduce test variability.

One of the primary issues in the interpretation of vehicle impact response data, observed from vehicle crash test events, is coping with variability. This vehicle response inconsistency generally causes test results to be unpredictable and makes CAE test validation work difficult as well. This paper, considering the uncertain characteristics of vehicle impact events, has implemented a stochastic assessment of vehicle NCAP response variation through a CAE vehicle impact model, and it has accomplished the three primary study objectives as stated follows: 1) Identify the response variation causing factors stochastically from various structural and environmental factor candidates and quantify the degree of their influences on crash response, 2) Develop a methodology for interpreting the significance of the factor effects in conjunction with vehicle impact mechanics and physics, and 3) Implement a stochastic improvement of the vehicle NCAP responses and their repeatability

In a new generation of unit injector (HEUI-Hydraulically Actuated and Electronically Controlled), a thin gap of oil film exists between the armature and solenoid. At low temperatures, high pressure slows the poppet causing poor injector performance. A CFD(Computational Fluid Dynamics) study with moving boundaries/meshes was undertaken to evaluate squeeze film behavior and determine optimum venting arrangement for improved injector performance.

A further development of the ETAB atomization and drop breakup model for high pressure-driven liquid fuel jets, has been developed, tuned and validated. As in the ETAB model, this breakup model reflects a cascade of drop breakups, where the breakup criterion is determined by the Taylor drop oscillator and each breakup event resembles experimentally observed breakup mechanisms. A fragmented liquid core due to inner-nozzle disturbances is achieved by injecting large droplets subject to this breakup cascade. These large droplets are equipped with appropriate initial deformation velocities in order to obtain experimentally observed breakup lengths. In contrast to the ETAB model which consideres only the bag breakup or the stripping breakup mechanism, the new model has been extended to include the catastrophic breakup regime. In addition, a continuity condition on the breakup parameters has lead to the reduction of one model constant.

The emerging need of building an efficient Electric Vehicle (EV) charging infrastructure requires the investigation of all aspects of Vehicle-Grid Integration (VGI), including the impact of EV charging on the grid, optimal EV charging control at scale, and communication interoperability. This paper presents a cloud-based simulation and testing platform for the development and Hardware-in-the-Loop (HIL) testing of VGI technologies. Although the HIL testing of a single charging station has been widely performed, the HIL testing of spatially distributed EV charging stations and communication interoperability is limited. To fill this gap, the presented platform is developed that consists of multiple subsystems: a real-time power system simulator (OPAL-RT), ISO 15118 EV Charge Scheduler System (EVCSS), and a Smart Energy Plaza (SEP) with various types of charging stations, solar panels, and energy storage systems.

High fidelity engine simulation requires realistic fuel models. Although typical automotive fuels consist of more than few hundreds of hydrocarbon species, researches show that the physical and chemical properties of the real fuels could be represented by appropriate surrogate fuel models. It is desirable to represent the fuel using the same set of physical and chemical surrogate components. However, when the reaction mechanisms for a certain physical surrogate component is not available, the chemistry of the unmatched physical component is described using that of a similar chemical surrogate component at the expense of accuracy. In order to reduce the prediction error while maintaining the computational efficiency, a method of on-the-fly reactivity adjustment (ReAd) of chemical reaction mechanism along with fuel re-distribution based on reactivity is presented and tested in this study.

Power split in Fuel Cell Hybrid Electric Vehicles (FCHEVs) has been controlled using different strategies ranging from rule-based to optimal control. Dynamic Programming (DP) and Model Predictive Control (MPC) are two common optimal control strategies used in optimization of the power split in FCHEVs with a trade-off between global optimality of the solution and online implementation of the controller. In this paper, both control strategies are developed and tested on a FC/battery vehicle model, and the results are compared in terms of total energy consumption. In addition, the effects of the MPC prediction horizon length on the controller performance are studied. Results show that by using the DP strategy, up to 12% less total energy consumption is achieved compared to MPC for a charge sustaining mode in the Urban Dynamometer Driving Schedule (UDDS) drive cycle.

Damping measurements on vehicle subsystems are rarely straightforward due to the complexity of the dynamic interaction of system joints, trim, and geometry. Various experimental techniques can be used for damping estimation, such as frequency domain modal analysis curve-fitting methods, time domain decay-rate methods, and other methods based on energy and wave propagation. Each method has its own set of advantages and drawbacks. This paper describes an analytical and an experimental comparison between two, widely used loss factor estimation techniques frequently used in Statistical Energy Analysis (SEA). The single subsystem Power Injection Method (PIM) and the Impulse Response Decay Method (IRDM) were compared using analytical models of a variety of simulated simple spring-mass-damper systems. Frequency averaged loss factor values were estimated from both methods for comparison.

Time-averaged temperatures at critical locations on the piston of a direct-fuel injected, two-stroke, 388 cm3, research engine were measured using an infrared telemetry device. The piston temperatures were compared to data [7] of a carbureted version of the two-stroke engine, that was operated at comparable conditions. All temperatures were obtained at wide open throttle, and varying engine speeds (2000-4500 rpm, at 500 rpm intervals). The temperatures were measured in a configuration that allowed for axial heat flux to be determined through the piston. The heat flux was compared to carbureted data [8] obtained using measured piston temperatures as boundary conditions for a computer model, and solving for the heat flux. The direct-fuel-injected piston temperatures and heat fluxes were significantly higher than the carbureted piston. On the exhaust side of the piston, the direct-fuel injected piston temperatures ranged from 33-73 °C higher than the conventional carbureted piston.

Single-cylinder engine experiments and computational fluid dynamics (CFD) modeling were used in this study to conduct a comprehensive evaluation of the accuracy of the modeling approach, with a focus on soot emissions. A semi-empirical soot model, the classic two-step Hiroyasu model with Nagle and Strickland-Constable oxidation, was used. A broad range of direct-injected (DI) combustion systems were investigated to assess the predictive accuracy of the soot model as a design tool for modern DI diesel engines. Experiments were conducted on a 2.5 liter single-cylinder engine. Combustion system combinations included three unique piston bowl shapes and seven variants of a common rail fuel injector. The pistons included a baseline “Mexican hat” piston, a reentrant piston, and a non-axisymmetric piston similar to the Volvo WAVE design. The injectors featured six or seven holes and systematically varied included angles from 120 to 150 degrees and hole sizes from 170 to 273 μm.

The combustion of highly boosted gasoline engines is limited by knocking combustion and pre-ignition. Therefore, a comprehensive modelling approach consisting of cycle-to-cycle simulation, reactor modelling with detailed chemistry and CFD-simulation was used to predict the knock initiation and to identify the source of pre-ignition. A 4-cylinder DISI test engine was set up and operated at low engine speeds and high boost pressures in order to verify the accuracy of the numerical approach. The investigations showed that there is a correlation between the knocking combustion and the very first combustion phase. The onset of knock was simulated with a stochastic reactor model and detailed chemistry. In parallel, measurements with an optical spark plug were carried out in order to identify the location of knock onset. The simulation results were in good agreement with the measurements. Deposits and oil/fuel-droplets are possible triggers of pre-ignition.

This paper describes the results of experiments that were performed using a Ground Research Vehicle (GRV) at the National Aeronautics and Space Administration's (NASA) Dryden Flight Research Center in Edwards, CA and a comparison with computational results. The GRV is a modified 1984 General Motors (GMC) van and measures 40 feet long and 9 feet high, with a base area of 83 by 83, and it weighs 10260 lbs and holds a crew of up to three. Air data is measured from a nose-boom, 2 global positioning (GPS) units, and an absolute Honeywell Pressure Transducer with 4 Electronic Signal Processor (ESP) scanners and 64 surface pressure ports. This allows for detailed measurements of the surface pressure profiles around the vehicle. The total vehicle drag is estimated from coast-down tests, while the pressure component of the drag force may be calculated by integrating the pressure profiles on the front and base of the vehicle.

The objective of this work is to perform a computer model based sensitivity analysis of parameters of an automotive air conditioning system to identify the critical parameters. Design of Experiment (DOE) and Analysis of Variance (ANOVA) techniques have been used to identify the critical parameters and their relative effects on the air conditioning system performance. The sensitivity analysis has been verified by running similar tests on an air conditioning system test stand (AC Test Stand).

This paper presents a method for optimization design of an engine mounting system subjected to some constraints. The engine center of gravity, the mount stiffness rates, the mount locations and/or their orientations with respect to the vehicle can be chosen as design variables, but some of them are given in advance or have limitations because of the packaging constraints on the mount locations, as well as the individual mount rate ratio limitations imposed by manufacturability. A computer program, called DynaMount, has been developed that identifies the optimum design variables for the engine mounting system, including decoupling mode, natural frequency placement, etc.. The degree of decoupling achieved is quantified by kinetic energy distributions calculated for each of the modes. Several application examples are presented to illustrate the validity of this method and the computer program.

This paper presents an overview of the connected controls and optimization system for vehicle dynamics and powertrain operation on a light-duty plug-in multi-mode hybrid electric vehicle developed as part of the DOE ARPA-E NEXTCAR program by Michigan Technological University in partnership with General Motors Co. The objective is to enable a 20% reduction in overall energy consumption and a 6% increase in electric vehicle range of a plug-in hybrid electric vehicle through the utilization of connected and automated vehicle technologies. Technologies developed to achieve this goal were developed in two categories, the vehicle control level and the powertrain control level. Tools at the vehicle control level include Eco Routing, Speed Harmonization, Eco Approach and Departure and in-situ vehicle parameter characterization.