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This investigation was aimed at measuring the relative performance of two spray-guided, single-cylinder, spark-ignited direct-injected (SIDI) engine combustion system designs. The first utilizes an outwardly-opening poppet, piezo-actuated injector, and the second a conventional, solenoid operated, inwardly-opening multi-hole injector. The single-cylinder engine tests were limited to steady state, warmed-up conditions. The comparison showed that these two spray-guided combustion systems with two very different sprays had surprisingly close results and only differed in some details. Combustion stability and smoke emissions of the systems are comparable to each other over most of the load range. Over a simulated Federal Test Procedure (FTP) cycle, the multi-hole system had 15% lower hydrocarbon and 18% lower carbon monoxide emissions.

A displacement-based CAE analysis is applied to liftgate chucking noise problems. A CAE simulation model of a small-size sport utility vehicle (SUV) is simulated with a set of realistic road loads as a time transient simulation. The model contains a trimmed vehicle, a liftgate and structural body-liftgate interface components such as the latch-striker wire, contact wedges and slam bumpers. Simulation design of experiments (DOE) is carried out with the model. As performance measures, the relative displacements at the contact points of the interface components are selected, since they are considered the direct cause of liftgate chucking. As design variables, body structure stiffness, liftgate stiffness, liftgate opening stiffness, stiffness characteristics of the interface components and additional liftgate mass are selected. Results of the simulation DOE is post-processed, and response surface models (RSM) are fit for the performance measures.

This paper outlines a process to assess the aerodynamic performance of different vehicle exterior surfaces. The initial section of the paper summarizes the details of white-light scanning process that maps entire vehicle to points in Cartesian co-ordinate system which is followed by the conversion of scanned points to theme surface. The concept of point-cloud modeling is employed to generate a smooth theme surface from scanned points. Theme surfaces thus developed are stitched to under-body/under-hood (UB/UH) parts of the base vehicle and the numerical simulations were carried out to understand the aerodynamic efficiency of the surfaces generated. Specifics of surface/volume mesh generated, boundary conditions imposed and numerical scheme employed are discussed in detail. Flow field over vehicle exterior is thoroughly analyzed. A comparison study highlighting the effect of front grilles in unblocked condition along with air-dam on flow field has been provided.

Understanding the flow characteristics and, especially, how the aerodynamic forces are influenced by the changes in the vehicle body shape, are very important in order to improve vehicle aerodynamics. One specific goal of aerodynamic shape optimization is to predict the local shape sensitivities for aerodynamic forces. The availability of a reliable and efficient sensitivity analysis method will help to reduce the number of design iterations and the aerodynamic development costs. Among various shape optimization methods, the Adjoint Method has received much attention as an efficient sensitivity analysis method for aerodynamic shape optimization because it allows the computation of sensitivity information for a large number of shape parameters simultaneously.

For a system which involves a fluid medium contained inside a deformable structure, such as a liquid fuel system, a simulation which couples the structure and fluid may be required depending on the operating conditions and system performance metric of interest. Simulation methods for fluid / structure interaction (FSI) have been gradually developed by CAE engineers with the advent of increased computer power. A robust fuel system design requires carefully designed components that can withstand all loadings it may experience. This paper presents both LS-Dyna's Arbitrary Lagrange-Euler (ALE) and Abaqus' Coupled Eulerian-Lagrange (CEL) methods for predicting the structural performance of a fuel tank system and demonstrates that a fuel tank systems and their components can be numerically evaluated before the products release.

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.

For many years, the computer aided math model has been the foundation for lowering cost and reducing time to market for many manufacturing industries. The automotive industry applies a variety of tools and methods to evaluate the expected vehicle performance to a forever expanding set of requirements. These mathematical predictions of performance are then repeated for both a set of design cycles and a multitude of vehicles in the product portfolio. This paper presents a CAE perspective of the unique problems of the large scale virtual vehicle engineering factory and a set of solutions. Different strategies to create the various complex math models required are explored. These strategies include using COTS FEA pre-processers, producing FEA models internal to the CAD tools, as well as custom built tools, macros and process automation tools.

In the automotive industry, CAE methods are now widely used to predict several functional characteristics and to develop designs that are first-time-capable to meet programs targets. The N&V area is one of the increasing key factors for a product differentiation; costumers expect not only more powerful and more fuel efficient but also less noisy engines. The oil pan is one of the bigger contributors to engine radiated noise and to diesel knocking, so that great attention is paid within GM to optimize oil pans of Diesel engines by following a CAE-based approach to achieve a “first-time-capable” design for this component. This allows focusing the subsequent N&V testing activities to pinpoint modifications mainly on those components with shorter lead time. This paper describes the key-steps that are executed to optimize the oil pan design by using CAE methods with the main intent of reducing its noise radiation.

Recent advancements in simulation software and computational hardware make it realizable to simulate a full vehicle system comprised of multiple sub-models developed in different modeling languages. The so-called, co-simulation allows one to develop a control strategy and evaluate various aspects of a vehicle system, such as fuel efficiency and vehicle drivability, in a cost-effective manner. In order to study the feasibility of the synchronized parallel processing in co-simulation this paper presents two co-simulation frameworks for a complete vehicle system with multiple heterogeneous subsystem models. In the first approach, subsystem models are co-simulated in a serial configuration, and the same sub-models are co-simulated in a parallel configuration in the second approach.

High-speed (12 kHz) imaging of combustion luminosity (enhanced by using a sodium fuel additive) has been analyzed and compared to crank angle resolved heat release rates and mass fraction burn profiles in a spray-guided spark-ignited direct-injection (SG-SIDI) optical single-cylinder engine. The addition of a sodium-containing additive to gasoline greatly increases the combustion luminosity, which allows unintensified high-speed (12 kHz) imaging of early partially premixed flame kernel growth and overall flame propagation with excellent signal-to-noise ratio for hundreds of consecutive engine cycles. Ignition and early flame kernel growth are known to be key to understanding and eliminating poor burn cycles in SG-SIDI engines.

A numerical and corresponding experimental study was undertaken to identify the ability to accurately predict combustion performance using our 3-D numerical tools for a direct-injection homogeneous-charge engine. To achieve a significant range of combustion rates, the evaluation was conducted for the engine operating with and without enhanced charge motion. Five charge motion configurations were examined, each having different levels of swirl and tumble flow leading to different turbulence generation and decay characteristics. A detailed CFD analysis provides insight into the in-cylinder flow requirements as well as the accuracy of the submodels. The in-cylinder air-fuel distribution, the mass-averaged swirl and tumble levels along with mean flow and turbulent kinetic energies are calculated throughout the induction and compression processes.

In 2006, the Insurance Institute for Highway Safety (IIHS) released a new Low Speed Bumper Test Protocol for passenger cars1. The new test protocol included the development of a deformable barrier that the vehicle would impact at low speeds. IIHS positioned the new barrier to improve correlation to low speed collisions in the field, and also to assess the ability of the bumper system to protect the vehicle from damage. The bumper system must stay engaged to the barrier to protect other vehicle components from damage. The challenge is to identify the bumper system design features that minimize additional cost and mass to keep engagement to the barrier. The results of the Design for Six Sigma analysis identified the design features that increase the stiffness of the bumper system enable it to stay engaged to the barrier and reduce the deflection.

Model-Based Development processes in the automotive industry typically use high-level modeling languages to build the reference models of embedded controllers. One can use formal verification tools to exhaustively verify these design models against their requirements, ensuring high quality models and a reduction in the cost and effort of functional testing. However, there is a gap, in terms of processes and tools, between the informal requirements and the formal specifications required by the verification tools. In this paper, we propose an approach that tries to bridge this gap by (i) identifying the verifiable requirements through a categorization process, (ii) providing a set of templates to easily express the verifiable requirements, and (iii) generating monitors that can be used as specifications in design verification tools. We demonstrate our approach using the Simulink Design Verifier tool for design verification of Simulink/Stateflow models.

Large hood mounted plastic trim components are subjected to complex and often extreme loading conditions. Typical loading conditions include solar and thermal cycling, as well as road and powertrain induced vibrations, aero lift and buffeting, and mechanical loads such as car wash. For the above components understanding and classifying the typical loading conditions is an essential and important step in achieving long term quality. This paper discusses different approaches to the design, analysis, development, and testing of plastic trim components. Samples of analysis and test results are presented to demonstrate how to identify and prevent the loss of the part function. Some useful guidelines and practices for addressing thermal expansion, dimensional variation, and redundancy in attachments are also discussed.

Recently, high-speed optical imaging data for a single operating point of a spray-guided gasoline engine has, along with the flamelet model and the G-equation theory, enabled the development of the new spark-ignition model SparkCIMM. Within its framework, detailed chemistry flamelet models capture the experimental feature of multiple localized ignition events along the excessively stretched and restriking spark channel, as well as the observations of non-spherical highly corrugated early turbulent flame fronts. The developed flamelet models account for the substantial turbulent fluctuations in equivalence ratio and enthalpy present under spray-guided conditions. A non-unity Lewis number formulation captures the deficient species diffusion into the highly curved flame reaction zone.

The urea injection is a key function in Urea-SCR NOx reduction system. As the tailpipe NOx emission standard becomes increasingly stringent, it is critical to diagnose the injection faults in order to guarantee the SCR DeNox functionality and performance. Particularly, a blocked injector may cause under-dosing of urea thus reduced DeNox functionality. Monitoring urea injection rate is one of the efficient methods for injection fault diagnosis. However, direct measurement of the urea mass flow is not feasible due to its high cost. This paper presents methods that are promising for detecting and isolating faults in urea injection by processing certain actuator signal and existing sensory measurements, e.g., the injector Pulse Amplitude Modulated (PAM) command and the pressure of the urea delivery line. No additional dedicated sensor is required. Three methods are discussed to detect urea injection system faults.

The sealing of a lift gate hinge to the body structure is necessary to avoid both the onset of corrosion and to avoid water intrusion into the interior compartment. The hinge-to-body interface typically involves horizontal metal-to-metal surface contact, creating the perfect environment for moisture entrapment and corrosion initiation. The choice of body panel material (uncoated (bare) steel vs. coated (galvanized) steel) drives different sealing approaches especially when considering corrosion avoidance.

Engineering has continuously strived to improve the vehicle development process to achieve high quality designs and quick to launch products. The design process has to have the tools and capabilities to help ensure both quick to the market product and a flawless launch. To achieve high fidelity and robust design, mistakes and other quality issues must be addressed early in the engineering process. One way to detect problems early is to use the math based modeling and simulation techniques of the analysis group. The correlation of the actual vehicle performance to the predictive model is crucial to obtain. Without high correlation, the change management process begins to get complicated and costs start to increase exponentially. It is critical to reduce and eliminate the risk in a design up front before tooling begins to kick off. The push to help achieve a high rate of correlation has been initiated by engineering management, seeing this as an asset to the business.

The sensor mounted on the door impact beam plays a major role in side impact events. The accelerations of side impact sensors are processed by sensing algorithms to make a decision on the air bag deployment. The sensing signal criterion for the deployable condition is a well understood process. However, the non-deployment sensing signal for the immunity to abuse conditions is a function of sensor attachment stiffness to the base structure. The base structure can be a door inner panel or door impact beam. In one of the production program, the acceleration based sensor attached to the impact beam showed immunity issues in the abusive door slams/opening to objects. Hence, the computer Aided Engineering (CAE) analysis was used to develop the sensor attachment criterion.

This paper describes an analytical methodology for predicting the fatigue life of a door system for check load durability cycles. A check stop load durability cycle occurs when a customer opens the door beyond the door detent position with a force applied on the check link or hinge check stops. This method combines Finite Element Analysis (FEA) model and fatigue code to compute the durability requirements. The FEA model consists of Door-in-White (DIW) on body with integrated hinge check link or independent check link. Nonlinear material, geometric and parts contact were considered for the door with body-in-white (BIW). Several door hinge designs, with integrated and independent check links, were investigated. Using the Von Mises stress and plastic strain from the above analysis, the fatigue life was predicted and compared with the test data. Integrating FEA and fatigue allows predicting the threshold total strain value, which is developed, for check load durability requirements.