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Optimization of the engine cold start is critical for gasoline direct injection (GDI) engines to meet increasingly stringent emission regulations, since the emissions during the first 20 seconds of the cold start constitute more than 80% of the hydrocarbon (HC) emissions for the entire EPA FTP75 drive cycle. However, Direct Injection Spark Ignition (DISI) engine cold start optimization is very challenging due to the rapidly changing engine speed, cold thermal environment and low cranking fuel pressure. One approach to reduce HC emissions for DISI engines is to adopt retarded spark so that engines generate high heat fluxes for faster catalyst light-off during the cold idle. This approach typically degrades the engine combustion stability and presents additional challenges to the engine cold start. This paper describes a CFD modeling based approach to address these challenges for the Ford 3.5L V6 EcoBoost engine cold start.

A systematic methodology has been employed to develop the Duratec 3.5L EcoBoost combustion system, with focus on the optimization of the combustion system including injector spray pattern, intake port design, piston geometry, cylinder head geometry. The development methodology was led by CFD (Computational Fluid Dynamics) modeling together with a testing program that uses optical, single-cylinder, and multi-cylinder engines. The current study shows the effect of several spray patterns on air-fuel mixing, in-cylinder flow development, surface wetting, and turbulence intensity. A few sets of injector spray patterns are studied; some that have a wide total cone angle, some that have a narrow cone angle and a couple of optimized injector spray patterns. The effect of the spray pattern at part load, full load and cold start operation was investigated and the methodology for choosing an optimized injector is presented.

This paper describes a CFD modeling based approach to address design challenges in GDI (gasoline direct injection) engine combustion system development. A Ford in-house developed CFD code MESIM (Multi-dimensional Engine Simulation) was applied to the study. Gasoline fuel is multi-component in nature and behaves very differently from the single component fuel representation under various operating conditions. A multi-component fuel model has been developed and is incorporated in MESIM code. To apply the model in engine simulations, a multi-component fuel recipe that represents the vaporization characteristics of gasoline is also developed using a numerical model that simulates the ASTM D86 fuel distillation experimental procedure. The effect of the multi-component model on the fuel air mixture preparations under different engine conditions is investigated. The modeling approach is applied to guide the GDI engine piston designs.

Noise concerns regarding snowmobiles have increased in the recent past. Current standards, such as SAE J192 are used as guidelines for government agencies and manufacturers to regulate noise emissions for all manufactured snowmobiles. Unfortunately, the test standards available today produce results with variability that is much higher than desired. The most significant contributor to the variation in noise measurements is the test surface. The test surfaces can either be snow or grass and affects the measurement in two very distinct ways: sound propagation from the source to the receiver and the operational behavior of the snowmobile. Data is presented for a known sound pressure speaker source and different snowmobiles on various test days and test surfaces. Relationships are shown between the behavior of the sound propagation and track interaction to the ground with the pass-by noise measurements.

Today's automotive and electronics technologies are evolving so rapidly that educators and industry are both challenged to re-educate the technological workforce in the new area before they are replaced with yet another generation. In early November 2009 Ford's Product Development senior management formally approved a proposal by the University of Detroit Mercy to transform 125 of Ford's “IC Engine Automotive Engineers” into “Advanced Electric Vehicle Automotive Engineers.” Two months later, the first course of the Advanced Electric Vehicle Program began in Dearborn. UDM's response to Ford's needs (and those of other OEM's and suppliers) was not only at the rate of “academic light speed,” but it involved direct collaboration of Ford's electric vehicle leaders and subject matter experts and the UDM AEV Program faculty.

The use of model-based software development in automotive applications has increased in recent years. Current vehicles contain millions of lines of code, and millions of dollars are spent each year fixing software issues. Most new features are software controlled and many times include distributed functionality, resulting in increased vehicle software content and accelerated complexity. To handle rapid change, OEMs and suppliers must work together to accelerate software development and testing. As development processes adapt to meet this challenge, model-based design can provide a solution. Model-based design is a broad development approach that is applied to a variety of applications in various industries. This paper reviews a project using the MATLAB/Simulink/Stateflow environment to complete a functional model of a low cost radio.

With the increasing demand for fuel efficient vehicles, technologies like superplastic forming (SPF) are being developed and implemented to allow for the utilization of lightweight automotive sheet materials. While forming under superplastic conditions leads to increased formability in lightweight alloys, such as aluminum, the slower forming times required by the technology can limit the technology to low to mid production levels. One problem that can increase forming time is the reduction of forming pressure due to pressurizing (forming) gas leaks, during the forming cycle, at the die/sheet/blankholder interface. Traditionally, such leaks have been successfully addressed through the use of a seal bead. However, for advanced die technologies that result in reduced cycle times (such as hot draw mechanical performing, which combine aspects of mechanical preforming of the sheet metal followed by SPF), the use of seal beads can restrict the drawing of sheet material into the forming die.

High pressure diesel sprays were visualized under vaporizing and combusting conditions in a constant-volume combustion vessel. Near-simultaneous visualization of vapor and liquid phase fuel distribution were acquired using a hybrid shadowgraph/Mie-scattering imaging setup. This imaging technique used two pulsed LED's operating in an alternative manner to provide proper light sources for both shadowgraph and Mie scattering. In addition, combustion cases under the same ambient conditions were visualized through high-speed combustion luminosity measurement. Two single-hole diesel injectors with same nozzle diameters (100μm) but different k-factors (k0 and k1.5) were tested in this study. Detailed analysis based on spray penetration rate curves, rate of injection measurements, combustion indicators and 1D model comparison have been performed.

Since transient vehicle HVAC computational fluids (CFD) simulations take too long to solve in a production environment, the goal of this project is to automatically create a lumped-parameter flow network from a steady-state CFD that solves nearly instantaneously. The data mining algorithm k-means is implemented to automatically discover flow features and form the network (a reduced order model). The lumped-parameter network is implemented in the commercial thermal solver MuSES to then run as a fully transient simulation. Using this network a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track localized temperatures near specific objects (such as equipment in vehicles).

A novel surrogate model is presented, which predicts the engine-out Particle Number (PN) emissions of a light-duty, spray-guided, turbo-charged, GDI engine. The model is developed through extensive CFD analysis, carried out using the Siemens Simcenter STAR-CD, and considers a range of part-load operating conditions and single-variable sweeps where control parameters such as start of injection and injection pressure are varied in isolation. The work is attached to the Ford-led APC6 DYNAMO project, which aims to improve efficiency and reduce harmful emissions from the next generation of gasoline engines. The CFD work focused on the air exchange, fuel spray and mixture preparation stages of the engine cycle. A combined Rosin-Rammler and Reitz-Diwakar model, calibrated over a wide range of injection pressure, is used to model fuel atomization and secondary droplets break-up.

Innovations in mobility are built upon a management of complex interactions between sub-systems and components. A need for CAE tools that are capable of system simulations is well recognized, as evidenced by a growing number of commercial packages. However impressive they are, the predictability of such simulations still rests on the representation of the base components. Among them, a wet clutch actuator continues to play a critical role in the next generation propulsion systems. It converts hydraulic pressure to mechanical force to control torque transmitted through a clutch pack. The actuator is typically modeled as a hydraulic piston opposed by a mechanical spring. Because the piston slides over a seal, some models have a framework to account for seal friction. However, there are few contributions to the literature that describe the effects of seals on clutch actuator behaviors.

Improvements in highway fuel economy require clever design and novel methods to reduce the drag coefficient. The integration of active flow control devices into vehicle design shows promise for greater reductions in drag coefficient. This paper examines the use of fluidic oscillators for separation control at the rear of an Ahmed vehicle model. A fluidic oscillator is a simple device that generates a sweeping jet output, similar to some windshield wiper spray nozzles, and is increasingly recognized as an efficient means to control separation. In this study, fluidic oscillators were used to blow unsteady air jets and control flow separation on rear boat-tail flaps, achieving drag reductions greater than 70 counts. The method appears to scale favorably to a larger model, and realistic effects such as a rolling road appear to have a small impact on the oscillator's control authority.

This study examines clutch-damper subsystem dynamics under transient excitation and validates predictions using a new laboratory experiment (which is the subject of a companion paper). The proposed models include multi-staged stiffness and hysteresis elements as well as spline nonlinearities. Several example cases such as two high (or low) hysteresis clutches in series with a pre-damper are considered. First, detailed multi-degree of freedom nonlinear models are constructed, and their time domain predictions are validated by analogous measurements. Second, key damping sources that affect transient events are identified and appropriate models or parameters are selected or justified. Finally, torque impulses are evaluated using metrics, and their effects on driveline dynamics are quantified. Dynamic interactions between clutch-damper and spline backlash nonlinearities are briefly discussed.

The effect of aerodynamically induced pre-swirl on the acoustic and performance characteristics of an automotive centrifugal compressor is studied experimentally on a steady-flow turbocharger facility. Accompanying flow separation, broadband noise is generated as the flow rate of the compressor is reduced and the incidence angle of the flow relative to the leading edge of the inducer blades increases. By incorporating an air jet upstream of the inducer, a tangential (swirl) component of velocity is added to the incoming flow, which improves the incidence angle particularly at low to mid-flow rates. Experimental data for a configuration with a swirl jet is then compared to a baseline with no swirl. The induced jet is shown to improve the surge line over the baseline configuration at all rotational speeds examined, while restricting the maximum flow rate. At high flow rates, the swirl jet increases the compressor inlet noise levels over a wide frequency range.

In this paper, a three-dimensional (3D) microstructure-based finite element modeling method (i.e., extrinsic modeling method) is developed, which can be used in examining the effects of porosity on the ductility/fracture of Mg castings. For this purpose, AM60 Mg tensile samples were generated under high-pressure die-casting in a specially-designed mold. Before the tensile test, the samples were CT-scanned to obtain the pore distributions within the samples. 3D microstructure-based finite element models were then developed based on the obtained actual pore distributions of the gauge area. The input properties for the matrix material were determined by fitting the simulation result to the experimental result of a selected sample, and then used for all the other samples’ simulation. The results show that the ductility and fracture locations predicted from simulations agree well with the experimental results.

This paper proposes a novel probabilistic approach for multidisciplinary design optimization (MDO) under uncertainty, especially for systems with feedback coupled analyses with multiple coupling variables. The proposed approach consists of four components: multidisciplinary analysis, Bayesian network, copula-based sampling, and design optimization. The Bayesian network represents the joint distribution of multiple variables through marginal distributions and conditional probabilities, and updates the distributions based on new data. In this methodology, the Bayesian network is pursued in two directions: (1) probabilistic surrogate modeling to estimate the output uncertainty given values of the design variables, and (2) probabilistic multidisciplinary analysis (MDA) to infer the distributions of the coupling and output variables that satisfy interdisciplinary compatibility conditions.

In an automotive cooling circuit, the wax melting process determines the net and time history of the energy transfer between the engine and its environment. A numerical process that gives insight into the mixing process outside the wax chamber, the wax melting process inside the wax chamber, and the effect on the poppet valve displacement will be advantageous to both the engine and automotive system design. A fully three dimensional, transient, system level simulation of an inlet controlled thermostat inside an automotive cooling circuit is undertaken in this paper. A proprietary CFD algorithm, Simerics-Sys®/PumpLinx®, is used to solve this complex problem. A two-phase model is developed in PumpLinx® to simulate the wax melting process. The hysteresis effect of the wax melting process is also considered in the simulation.

Compression molded SMC composed of chopped carbon fiber and resin polymer which balances the mechanical performance and manufacturing cost presents a promising solution for vehicle lightweight strategy. However, the performance of the SMC molded parts highly depends on the compression molding process and local microstructure, which greatly increases the cost for the part level performance testing and elongates the design cycle. ICME (Integrated Computational Material Engineering) approaches are thus necessary tools to reduce the number of experiments required during part design and speed up the deployment of the SMC materials. As the fundamental stage of the ICME workflow, commercial software packages for SMC compression molding exist yet remain not fully validated especially for chopped fiber systems. In the present study, SMC plaques are prepared through compression molding process.

Ford Motor Company’s assembly plants build vehicles in a certain sequence. The planned sequence for the plant’s trim and final assembly area is developed centrally and is sent to the plant several days in advance. In this work we present the study of two cases where the plant changes the planned sequence to cope with production constraints. In one case, a plant pulls ahead two-tone orders that require two passes through the paint shop. This is further complicated by presence in the body shop area of a unidirectional rotating tool that allows efficient build of a sequence “A-B-C” but heavily penalizes a sequence “C-B-A”. The plant changes the original planned sequence in the body shop area to the one that satisfies both pull-ahead and rotating tool requirements. In the other case, a plant runs on lean inventories. Material consumption is tightly controlled down to the hour to match with planned material deliveries.

For achieving viable mass customization of products, product configuration is often performed that requires deep understanding on the impact of product features and feature combinations on customers’ purchasing behaviors. Existing literature has been traditionally focused on analyzing the impact of common customer demographics and engineering attributes with discrete choice modeling approaches. This paper aims to expand discrete choice modeling through the incorporation of optional product features, such as customers’ positive or negative comments and their satisfaction ratings of their purchased products, beyond those commonly used attributes. The paper utilizes vehicle as an example to highlight the range of optional features currently underutilized in existing models. First, data analysis techniques are used to identify areas of particular consumer interest in regards to vehicle selection.