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Magnesium and aluminum alloys offer lightweighting opportunities in automotive applications. Joining of dissimilar materials, however, generally requires methods that do not involve fusion. This paper explores the use of self-pierce riveting (SPR) to join magnesium to aluminum alloys for structural and closure applications. The preliminary results indicate that SPR is a viable option for joining aluminum extrusions to magnesium die castings, as well as stamped sheet aluminum to quick-plastic-formed (QPF) sheet magnesium.

As mass reduction becomes an increasingly important enabler for fuel economy improvement, having a robust structural development process that can comprehend Vehicle Dynamics-specific requirements is correspondingly important. There is a correlation between the stiffness of the body structure and the performance of the vehicle when evaluated for ride and handling. However, an unconstrained approach to body stiffening will result in an overly-massive body structure. In this paper, the authors employ loads generated from simulation of quasi-static and dynamic vehicle events in ADAMS, and exercise structural finite element models to recover displacements and deflected shapes. In doing so, a quantitative basis for considering structural vehicle dynamics requirements can be established early in the design/development process.

Experimental decklids for the Cadillac STS sedan were made with Al AA5083 sheet outer panels and Mg AZ31B sheet inner panels using regular-production forming processes and hardware. Joining and coating processes were developed to accommodate the unique properties of Mg. Assembled decklids were evaluated for dimensional accuracy, slam durability, and impact response. The assemblies performed very well in these tests. Explicit and implicit finite element simulations of decklids were conducted, and showed that the Al/Mg decklids have good stiffness and strength characteristics. These results suggest the feasibility of using Mg sheet closure panels from a structural perspective.

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).

This paper presents a combined numerical and experimental investigation of the characteristics of spark discharge in a spark-ignition engine. The main objective of this work is to gain insights into the spark discharge process and early flame kernel development. Experiments were conducted in an inert medium within an optically accessible constant-volume combustion vessel. The cross-flow motion in the vessel was generated using a previously developed shrouded fan. Numerical modeling was based on an existing discharge model in the literature developed by Kim and Anderson. However, this model is applicable to a limited range of gas pressures and flow fields. Therefore, the original model was evaluated and improved to predict the behavior of spark discharge at pressurized conditions up to 45 bar and high-speed cross-flows up to 32 m/s. To accomplish this goal, a parametric study on the spark channel resistance was conducted.

General Motors has developed an all-new Ecotec 1.5 L range extender engine for use in the 2016 next generation Voltec propulsion system. This engine is part of a new Ecotec family of small displacement gasoline engines introduced in the 2015 model year. Major enhancements over the range extender engine in the current generation Voltec propulsion system include the adoption of direct injection (DI), cooled external exhaust gas recirculation (EGR), and a high 12.5:1 geometric compression ratio (CR). Additional enhancements include the adoption of high-authority phasers on both the intake and exhaust camshafts, and an integrated exhaust manifold (IEM). The combination of DI with cooled EGR has enabled significant thermal efficiency gains over the 1.4 L range extender engine in the current generation Voltec propulsion system at high engine loads.

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.

In order to extend the operability limit of the gasoline compression ignition (GCI) engine, as an avenue for low temperature combustion (LTC) regime, the effects of parametric variations of engine operating conditions on the performance of six-stroke GCI (6S-GCI) engine cycle are numerically investigated, using an in-house 3D CFD code coupled with high-fidelity physical sub-models along with the Chemkin library. The combustion and emissions were calculated using a skeletal chemical kinetics mechanism for a 14-component gasoline surrogate fuel. Authors’ previous study highlighted the effects of the variation of injection timing and split ratio on the overall performance of 6S-GCI engine and the unique mixing-controlled burning mode of the charge mixtures during the two additional strokes. As a continuing effort, the present study details the parametric studies of initial gas temperature, boost pressure, fuel injection pressure, compression ratio, and EGR ratio.

Increasing regulatory demand for efficiency has led to development of novel combustion modes such as HCCI, GCI and RCCI for gasoline light duty engines. In order to realize HCCI as a compression ignition combustion mode system, in-cylinder compression temperatures must be elevated to reach the autoignition point of the premixed fuel/air mixture. This should be co-optimized with appropriate fuel formulations that can autoignite at such temperatures. CFD combustion modeling is used to model the auto ignition of gasoline fuel under compression ignition conditions. Using the fully detailed fuel mechanism consisting of thousands of components in the CFD simulations is computationally expensive. To overcome this challenge, the real fuel is represented by few major components of create a surrogate fuel mechanism. In this study, 9 variations of gasoline fuel sets were chosen as candidates to run in HCCI combustion mode.

Autonomous vehicle operation is dependent upon accurate position estimation and thus a major concern of implementing the autonomous navigation is obtaining robust and accurate data from sensors. This is especially true, in case of Inertial Measurement Unit (IMU) sensor data. The IMU consists of a 3-axis gyro, 3-axis accelerometer, and 3-axis magnetometer. The IMU provides vehicle orientation in 3D space in terms of yaw, roll and pitch. Out of which, yaw is a major parameter to control the ground vehicle’s lateral position during navigation. The accelerometer is responsible for attitude (roll-pitch) estimates and magnetometer is responsible for yaw estimates. However, the magnetometer is prone to environmental magnetic disturbances which induce errors in the measurement.

In this paper, a model-based linear estimator and a non-linear control law for an Fe-zeolite urea-selective catalytic reduction (SCR) catalyst for heavy duty diesel engine applications is presented. The novel aspect of this work is that the relevant species, NO, NO2 and NH3 are estimated and controlled independently. The ability to target NH3 slip is important not only to minimize urea consumption, but also to reduce this unregulated emission. Being able to discriminate between NO and NO2 is important for two reasons. First, recent Fe-zeolite catalyst studies suggest that NOx reduction is highly favored by the NO 2 based reactions. Second, NO2 is more toxic than NO to both the environment and human health. The estimator and control law are based on a 4-state model of the urea-SCR plant. A linearized version of the model is used for state estimation while the full nonlinear model is used for control design.

Compressed natural gas (CNG) currently is used as an alternative fuel for internal combustion engines in motor vehicles. This paper presents results of an analysis of leaks from a model isolated section of CNG fuel system. Discharge of CNG was modeled as vent flow of a real gas hydrocarbon mixture through an orifice from a reservoir with finite volume. Pressures typically used in CNG fuel systems result in choked flow for gas venting directly to atmosphere, producing an under-expanded, momentum-dominated, turbulent free jet with well defined velocity and concentration fields. This paper presents results of analyses of reservoir pressure decay, and vent flow and concentrations fields for CNG venting from a pressurized reservoir into the atmosphere. A combination of empirically-derived analytical relationships and detailed two-dimensional high resolution computational fluid dynamic modeling was used to determine the velocity and concentrations fields of the resulting CNG jet.

A comprehensive experimental and theoretical approach was undertaken to understand the phenomenon of pre-ignition and to assess parameters to improve or even eliminate it completely. Oil mixing with fuel was identified as the leading theory of self ignition of the fuel. End of compression temperature has to meet a minimum level for pre-ignition to take place. In this work a comprehensive list of parameters were identified that have a direct and crucial role in the onset of pre-ignition including liner wetting, injection targeting, stratification, mixture motion and oil formulation. Many secondary effects were identified including ring dynamics, ring tension, spark plug electrode temperature and coolant temperature. CFD has been extensively used to understand test results including wall film, A/F ratio distribution and temperature at the end of compression when looked at in the context of fuel evaporation and mixing.

As the new features for driver assistance and active safety systems are growing rapidly in vehicles, the simulation within a virtual environment has become a necessity. The current active safety system consists of Electronic Control Units (ECUs) which are coupled to camera and radar sensors. Two methods of implementation exists, integrated sensors with control modules or separation of sensors form control modules. The subsystem integration testing poses new challenges for virtual environment for simulation of active safety features. The comprehensive simulation environment for integration testing consists of chassis controls, powertrain, driver assistance, body and displays controllers. Additional complexity in the system is the serial communication strategy. Multiple communication protocols such as GMLAN, LIN, standard CAN, and Flexray could be present within the same vehicle topology.

There is an increasing demand in automated manufacturability analysis of metal castings at the initial stages of their design. This paper presents a system developed for virtual manufacturability analysis of casting components. The system can be used by a casting designer to evaluate manufacturability of a part designed for various manufacture processes including casting, heat treatment, and machining. The system uses computational geometrics and geometric reasoning to extract manufacturing features and geometry characteristics from a part CAD model. It uses an expert system and a design database consisting of metal casting, heat treatment and machining process knowledge and rules to present manufacturability analysis results and advice to the designer. Application of the system is demonstrated for the manufacturability assessment of automotive cast aluminum components.

Three different acoustic finite element models of an automobile passenger compartment are developed and experimentally assessed. The three different models are a traditional model, an improved model, and an optimized model. The traditional model represents the passenger and trunk compartment cavities and the coupling between them through the rear seat cavity. The improved model includes traditional acoustic models of the passenger and trunk compartments, as well as equivalent-acoustic finite element models of the front and rear seats, parcel shelf, door volumes, instrument panel, and trunk wheel well volume. An optimized version of the improved acoustic model is developed by modifying the equivalent-acoustic properties. Modal analysis tests of a vehicle were conducted using loudspeaker excitation to identify the compartment cavity modes and sound pressure response to 500 Hz to assess the accuracy of the acoustic models.

At elevated temperatures, such as those encountered under race track or fade test conditions, the closed-form solution to the lumped capacitance model for characterizing brake cooling (fitted to a standard cooling test temperature range) tends to break down and provide an inaccurate representation of brake rotor cooling behavior. Accurate prediction of cooling is fundamental to brake system component sizing and selection of materials at the early stages of a vehicle program; this is especially true of a high performance vehicle with track performance requirements. To this end, alternative approaches to characterizing brake cooling have been examined to determine their suitability for use in measurement and simulation of brake performance.

During sheet metal forming, the friction and surface roughness change as the sheet slides, bends and stretches against the tools. This study assessed evolution of friction and surface roughness changes on aluminum sheet with two surface finish conditions, mill finish (MF) and electron discharge texture (EDT), in both the longitudinal and the transverse rolling directions of the sheet. The sheets were tested using a three pin Draw Bead Simulator (DBS). Surface roughness of the sheet evolved as a result of bending at the first shoulder, reverse bending at the middle pin, bending at the second shoulder and unbending at the exit. Stretching conditions and sheet-pin contact were also varied to see the impact on surface roughness. In general, the largest surface roughness change for the transverse direction was observed at the convex side of the exit shoulder pin and on the convex side of the first shoulder for the longitudinal direction.

Aluminum sheet is commercially available in three surface finishes, mill finish (MF), electric discharge texture (EDT), and dull finish (DF). This surface finish impacts the friction behavior during sheet metal forming. A study was done to compare ten commercially available sheet samples from several suppliers. The friction behavior was characterized in the longitudinal and transverse directions using a Draw Bead Simulator (DBS) test, resulting in a coefficient of friction (COF) value for each material. Characterization of the friction behavior in each direction provides useful data for formability analysis. To quantitatively characterize the surface finish, three-dimensional MicroTexture measurements were done with a WYKO NT8000 instrument. In general, the MF samples have the smoothest surface, with Sa values of 0.20-0.30 μm and the lowest COF values. The EDT samples have the roughest surface, with Sa values of 0.60-1.00 μm, and the highest COF values.

The preform annealing process is a two-stage stamping method for shaping non age-hardenable (i.e. 5000 series) aluminum sheet panels in which the panel is heat treated in between the two steps to improve overall formability of the material. The intermediate annealing heat treatment eliminates the cold work accumulated in the material during the first draw. The process enables the ability to form more complex parts than a conventional aluminum stamping process. A demonstration of local annealing for this process was conducted to form a one-piece aluminum liftgate inner panel for a large sport utility vehicle using the steel product geometry without design concessions. In prior work, this process was demonstrated by placing the entire panel in a convection oven for several minutes to completely anneal the cold work.