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An integrated engineering approach using computer modeling, laboratory and vehicle testing enabled the Ford GT engineering team to achieve supercar thermal management performance within the aggressive program timing. Theoretical and empirical test data was used during the design and development of the engine cooling system. The information was used to verify design assumptions and validate engineering efforts. This design approach allowed the team to define a system solution quickly and minimized the need for extensive vehicle level testing. The result of this approach was the development of an engine cooling system that adequately controls air, oil and coolant temperatures during all driving and environmental conditions.

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.

Model validation is a process to assess the validity and predictive capabilities of a computer model by comparing simulation results with test data for its intended use of the model. One of the key difficulties for model validation is to evaluate the quality of a computer model at different test configurations in design space, and interpolate or extrapolate the evaluation results to untested new design configurations. In this paper, an integrated model interpolation and extrapolation framework based on Bayesian inference and Response Surface Models (RSM) is proposed to validate the designs both within and outside of the original design space. Bayesian inference is first applied to quantify the distributions' hyper-parameters of the bias between test and CAE data in the validation domain. Then, the hyper-parameters are extrapolated from the design configurations to untested new design. They are then followed by the prediction interval of responses at the new design points.

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.

With the increasing level of electrification of on-road, off-road and stationary applications, use of larger lithium-ion battery packs has become essential. These packs require large capital investments on the order of millions of dollars and pose a significant risk of self-annihilation without rigorous safety evaluation and management. Testing these larger battery packs to validate design changes can be cost prohibitive. A reliable numerical simulation tool to predict battery thermal runaway under various abuse scenarios is essential to engineer safety into the battery pack design stage. A comprehensive testing & simulation workflow has been established to calibrate and validate the numerical modeling approach with the test data for each of the individual sub model - electrochemical, internal short circuit and thermal abuse model. A four-equation thermal abuse model was built and validated for lithium-ion 21700 form factor cylindrical cells using NCA cathodes.

A framework to study the response of seated operators to whole-body vibration (WBV) is presented in this work. The framework consists of (i) a six-degree-of-freedom man-rated motion platform to play back ride files of typical heavy off-road machines; (ii) an optical motion capture system to collect 3D motion data of the operators and the surrounding environment (seat and platform); (iii) a computer skeletal model to embody the tested subjects in terms of their body dimensions, joint centers, and inertia properties; (iv) a marker placement protocol for seated positions that facilitates the process of collecting data of the lower thoracic and the lumbar regions of the spine regardless of the existence of the seatback; and (v) a computer human model to solve the inverse kinematics/dynamic problem for the joint profiles and joint torques. The proposed framework uses experimental data to answer critical questions regarding human response to WBV.

A four-stroke, spark-ignition engine is described that seeks to achieve high expansion ratio and low throttling losses at light load, whilst retaining good knock resistance at full load operation and without the need for expensive mechanical changes to the engine. The engine does, however, incorporate a second inlet (transfer) valve and associated transfer port linked to the intake port. The timing of the transfer valve is different from that of the main inlet valve. Load modulation is achieved by control of the gas outflow from the transfer port. A computer model of the engine is first validated against measured data from a conventional engine. Comparisons are made of incylinder pressure at part load conditions, total air flowrate through the engine and intake port air velocities as a function of crank angle position.

Computer simulation of the behavior of the automotive cooling system is becoming increasingly common, so as to reduce the dependency on costly testing. The simulation of transient cooling system behavior has become easier with the use of 1-D simulation tools. However, accurate prediction of transient coolant temperature after thermostat operation has been limited by the difficulty in accurately modeling the behavior of the automotive thermostat. Physical models of the thermostat are often inaccurate due to the complexity of the thermostat. Therefore an empirical model has been developed, which can be used to model any automotive thermostat, once a few simple tests have been conducted on the part. This thermostat model can be used in conjunction with a 1-D flow simulation tool to predict coolant transient temperature response during thermostat operation.

The performance of five positive k-factor injector tips has been assessed in this work by analyzing a comprehensive set of injected mass, momentum, and spray measurements. Using high speed shadowgraphs of the injected diesel plumes, the sensitivities of measured vapor penetration and dispersion to injection pressure (100-250MPa) and ambient density (20-52 kg/m3) have been compared with the Naber-Siebers empirical spray model to gain understanding of second order effects of orifice diameter. Varying in size from 137 to 353μm, the orifice diameters and corresponding injector tips are appropriate for a relatively wide range of engine cylinder sizes (from 0.5 to 5L). In this regime, decreasing the orifice exit diameter was found to reduce spray penetration sensitivity to differential injection pressure. The cone angle and k-factored orifice exit diameter were found to be uncorrelated.

In this paper, we introduce a numerically stable 2D computer model for sheet metal forming analysis based on the membrane theory. It simulates both axisymmetrical and plane strain cases with various restraining and friction conditions. We implemented a more realistic material model that accounts for cyclic loading and unloading. Also, the difficult frictional force reversal problem has been overcome. A simulation package released within Ford Motor Company has proven robust and accurate for applications to industrial cases.

A one-dimensional, two layer computational model was developed to predict the behavior of a clean and particulate-loaded catalyzed wall-flow diesel particulate filter (CPF). The model included the mechanisms of particle deposition inside the CPF porous wall and on the CPF wall surface, the exhaust flow field and temperature field inside the CPF, as well as the particulate catalytic oxidation mechanisms accounting for the catalyst-assisted particulate oxidation by the catalytic coating in addition to the conventional particulate thermal oxidation. The paper also develops the methodology for calibrating and validating the model with experimental data. Steady state loading experiments were performed to calibrate and validate the model.

Next generation vehicles are under environmental and economic pressure to reduce emissions and increase fuel economy, while maintaining the same ride and performance characteristics of present day combustion engine automobiles. This has prompted researchers to investigate hybrid vehicles as one possible solution to this challenge. At Southwest Research Institute (SwRI), a unique parallel hybrid drivetrain was designed and prototyped. This hybrid drivetrain alleviates the disadvantages of series hybrid drivetrains by directly coupling the driving wheels to two power sources, namely an engine and an electric motor. At the same time, the design allows the engine speed to be decoupled from the vehicle speed, allowing the engine to operate at its most efficient state. This paper describes the drivetrain, its components, and the test stand that was assembled to test the parallel hybrid drivetrain.

In vehicle design, response surface model (RSM) is commonly used as a surrogate of the high fidelity Finite Element (FE) model to reduce the computational time and improve the efficiency of design process. However, RSM introduces additional sources of uncertainty, such as model bias, which largely affect the reliability and robustness of the prediction results. The bias of RSM need to be addressed before the model is ready for extrapolation and design optimization. This paper further investigates the Bayesian inference based model extrapolation method which is previously proposed by the authors, and provides a systematic and integrated stochastic bias corrected model extrapolation and robustness design process under uncertainty. A real world vehicle design example is used to demonstrate the validity of the proposed method.

An experimental and modeling study was conducted to study the passive regeneration of a catalyzed particulate filter (CPF) by the oxidation of particulate matter (PM) via thermal and Nitrogen dioxide/temperature-assisted means. Emissions data in the exhaust of a John Deere 6.8 liter, turbocharged and after-cooled engine with a low-pressure loop EGR and a diesel oxidation catalyst (DOC) - catalyzed particulate filter (CPF) in the exhaust system was measured and used for this study. A series of experiments was conducted to evaluate the performance of the DOC, CPF and DOC+CPF configurations at various engine speeds and loads.

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.

It has been shown within the catalyst industry that the emission performance with higher cell density technology and therefore with higher specific geometric area is improved. The focus of this study was to compare the overall performance of high cell density catalysts, up to 1600cpsi, using a MY 2001 production vehicle with a 4.7ltr.V8 engine. The substrates were configured to be on the edge of the design capability. The goal was to develop cost optimized systems with similar emission and back pressure performance, which meet physical and production requirements. This paper will present the results of a preliminary computer simulation study and the final emission testing of a production vehicle. For the pre-evaluation a numerical simulation model was used to compare the light-off performance of different substrate designs in the cold start portion of the FTP test cycle.

The continued increase in complexity of automotive electronics has further necessitated for systems to be designed for optimal testing and servicing in the field. Locating failures within complex, interactive electronic systems can create conditions of both high warranty costs and customer dissatisfaction. Decisions about levels of system integration and diagnostics early in the design phases are fundamental parts of these considerations and are addressed in this paper. The approach focuses on projecting field repair rates and maintenance costs using a Monte Carlo computer simulation method given various component parameters such as part costs, reliability, labor time, and field diagnostic strategies. Results of the projection technique were shown to be quite accurate in projecting field warranty costs of a complex electronic system.

This paper presents a Computational Fluid Dynamic(CFD) model for the oil pump simulations aimed at better understanding the flow characteristics for improving their designs and reducing product development cycles. Several advanced numerical technologies have been developed to handle the complex geometries of oil pumps and the moving interfaces between the rotating and stationary parts. Two basic oil pump configurations, a vane oil pump and a gerotor oil pump, have been studied with the present method. The numerical results are compared with the existing experimental data.

Computational fluid dynamics of gas-fueled large-bore spark ignition engines with pre-chamber ignition can speed up the design process of these engines provided that 1) the reliability of the results is not affected by poor meshing and 2) the time cost of the meshing process does not negatively compensate for the advantages of running a computer simulation. In this work a flame propagation model that runs with arbitrary hybrid meshes was developed and coupled with the KIVA4-MHI CFD solver, in order to address these aims. The solver follows the G-Equation level-set method for turbulent flame propagation by Tan and Reitz, and employs improved numerics to handle meshes featuring different cell types such as hexahedra, tetrahedra, square pyramids and triangular prisms. Detailed reaction kinetics from the SpeedCHEM solver are used to compute the non-equilibrium composition evolution downstream and upstream of the flame surface, where chemical equilibrium is instead assumed.