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In order to increase the efficiency of automotive turbochargers at low speed without compromising the performance at maximum boost conditions, variable geometry compressor (VGC) systems, based on either variable inlet guide vanes or variable geometry diffusers, have been recently considered as a future design option for automotive turbochargers. This work presents a modeling, analysis and optimization study for a Diesel engine equipped with a variable geometry compressor that help understand the potentials of such technology and develop control algorithms for the VGC systems,. A cycle-averaged engine system model, validated on experimental data, is used to predict the most important variables characterizing the intake and exhaust systems (i.e., mass flow rates, pressures, temperatures) and engine performance (i.e., torque, BMEP, volumetric efficiency), in steady-state and transient conditions.

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.

To cope with the increasing number of advanced features (e.g., smart-phone integration and side-blind zone alert.) being deployed in vehicles, automotive manufacturers are designing flexible hardware architectures which can accommodate increasing feature content with as fewer as possible hardware changes so as to keep future costs down. In this paper, we propose a formal and quantitative definition of flexibility, a related methodology and a tool flow aimed at maximizing the flexibility of an automotive hardware architecture with respect to the features that are of greater importance to the designer. We define flexibility as the ability of an architecture to accommodate future changes in features with no changes in hardware (no addition/replacement of processors, buses, or memories). We utilize an optimization framework based on mixed integer linear programming (MILP) which computes the flexibility of the architecture while guaranteeing performance and safety requirements.

Standard CFD methods require a mesh that fits the boundaries of the computational domain. For a complex geometry the generation of such a grid is time-consuming and often requires modifications to the model geometry. This paper evaluates the Immersed Boundary (IB) approach which does not require a boundary-conforming mesh and thus would speed up the process of the grid generation. In the IB approach the CAD surfaces (in Stereo Lithography -STL- format) are used directly and this eliminates the surface meshing phase and also mitigates the process of the CAD cleanup. A volume mesh, consisting of regular, locally refined, hexahedrals is generated in the computational domain, including inside the body. The cells are then classified as fluid, solid and interface cells using a simple ray-tracing scheme. Interface cells, correspond to regions that are partially fluid and are intersected by the boundary surfaces.

Fast-running metamodels (surrogates or response surfaces) that approximate multivariate input/output relationships of time-consuming CAE simulations facilitate effective design trade-offs and optimizations in the vehicle development process. While the cross-validated nonparametric metamodeling methods are capable of capturing the highly nonlinear input/output relationships, it is crucial to ensure the adequacy of the metamodel error estimates. Moreover, in order to circumvent the so-called curse-of-dimensionality in constructing any nonlinear multivariate metamodels from a realistic number of expensive simulations, it is necessary to reliably eliminate insignificant inputs and consequently reduce the metamodel prediction error by focusing on major contributors. This paper presents a robust data-adaptive nonparametric metamodeling procedure that combines a convergent variable screening process with a robust 2-level error assessment strategy to achieve better metamodel accuracy.

Twent-two participants of varying ages detected roadside targets in two consecutive dynamic evaluations of a horizontally swiveling headlamp vehicle and a vehicle with the same headlamps that did not swivel. Participants detected targets as they drove unlighted low-speed public roads. Scenarios encountered were intersection turns, and curves with approximate radii of 70-90m, 120-140m, 170-190m, and 215-220m. Results from the first study found improved detection distances from the swiveling headlamps in left curves, but unexpectedly decreased detection distances in larger radius right hand curves. The swiveling algorithm was altered for the second study, and the headlamps used did not have the same beam pattern as in the first study. Results from the second study again found improved detection distances from the swiveling headlamps while in the larger radius right hand curves fixed and swivel were not statistically different.

This paper presents a simplified approach for formability simulation of automotive body structural sections in the early design stage of vehicle development process. Plane strain approach is investigated for its applicability and accuracy by comparing the analytical results with the measured results of automotive body side panel. The plane strain approach was tried based on the fact that for a certain section location of a stamped panel, the minor strains are relatively small and negligible compared to the major strains. The state of plane strain can be induced mainly through symmetry and applied boundary conditions. This approach is both cost effective and time saving for analyzing sheet metal formability in early vehicle development stage, since only few sections of the entire panel need be analyzed.

This study investigates a methodology in which the general public's subjective interpretation of vehicle handling and performance can be predicted. Several vehicle handling measurements were acquired, and associated metrics calculated, in a controlled setting. Human evaluators were then asked to drive and evaluate each vehicle in a winter driving school setting. Using the acquired data, multiple linear regression and artificial neural network (ANN) techniques were used to create and refine mathematical models of human subjective responses. It is shown that artificial neural networks, which have been trained with the sets of objective and subjective data, are both more accurate and more robust than multiple linear regression models created from the same data.

An integrated stochastic design framework that facilitates practical applications involving time-consuming CAE simulations is described. The probabilistic performance measure that addresses stochastic uncertainties in CAE modeling and simulations is used to support design decision-making. Two enabling metamodeling methods using cross-validated radial basis functions (CVRBF) and a corresponding uniform sampling method are introduced to approximate highly nonlinear CAE model input/output relationships. A vehicle restraint system example is used to demonstrate the effectiveness of the proposed framework and enabling techniques.

The Auto/Steel Partnership Corrosion Project Team has completed a perforation corrosion test program consisting of on-vehicle field exposures and various accelerated tests. Steel sheet products with eight combinations of metallic and organic coatings were tested, utilizing a simple crevice coupon design. On-vehicle exposures were conducted in St. John's and Detroit for up to seven years to establish a real-world performance standard. Identical test specimens were exposed to the various accelerated tests, and the results were compared to the real-world standard. This report documents the results of these tests, and compares the accelerated test results (including SAE J2334, GM9540P, Ford APGE, CCT-I, ASTM B117, South Florida Modified Volvo, and Kure Beach (25-meter) exposures) to the on-vehicle tests. The results are compared in terms of five criteria: extent of corrosion, rank order of material performance, degree of correlation, acceleration factor, and control of test environment.

As one of many pack-level battery simulation approaches developed within the General Motors-led Computer-Aided Engineering of Automotive Batteries (CAEBAT) Phase 1 project, the system approach treats the entire battery pack as a dynamic system which includes multiple engineering disciplines for simulation. It is the most efficient approach of all the CAEBAT battery pack-level approaches in terms of computational time and resources. This paper reports the application of the system approach for a 24-cell liquid-cooled prototype battery pack. It also summarizes the verification of the approach by comparing the simulation results with the measurement data. The results using the system approach are found to have a very good agreement with the measurements.

It has the aim to discuss the evolution of electronics components, integrated circuits, new transistors concepts and associate its importance in the automotive modules. Today, the challenge is to have devices which consume less power, suitable for high-energy radiation environment, less parasitic capacitances, high speed, easier device isolation, high gain, easier scale-down of threshold voltage, no latch-up and higher integration density. The improvement of those characteristics mentioned and others in the electronic devices enable the automotive industry to have a more robust product and give the possibility to integrate new features in comfort, safety, infotainment and telematics modules. Finally, the intention is to discuss advanced structures, such as the silicon-on-insulator (SOI) and show how it affects the electronics modules applied for the automotive area.

The so-called Modified Martempering discussed in this work differs from the standard martempering by that the temperature of the quenching bath is below the Ms point. In spite of the fact the lower temperature increases the severity of quenching, this also usually avoids the bainite formation, and by this reason, it is possible to make a fair comparison between different processes, which result in different microstructures. The present study shows the results in terms of mechanical properties, impact resistance in special of a cold work tool steel class, after being heat treated by the isothermal modified martempering process, as well as a comparison with the conventional quenching and tempering process and the austempering as well.

Software development tools can be used in conjunction with test automation tools to validate controller software. Test automation tools must have an open architecture to interface with all the different software and hardware components, within a control validation project. Therefore software development tools like Matlab/Simulink will be able to exchange data via real time interface software with test automation tools. The test automation tool must be flexible to pass data back and forth from/to Microsoft standard software programs like Excel.

The largest application of mercury in automotive applications occurs in underhood and trunk lamp activation switches. A reduction of mercury in this application will have a significant impact on automotive mercury usage. Using environmentally conscious design and manufacturing principles, this paper will investigate functional alternatives for the activation of underhood (U/H) and trunk lamp applications. Five alternatives to perform the activation function will be analyzed in four areas over their life cycles: Environmental Economic Engineering Manufacturing Each alternative will be ranked on criteria in each of these four areas using documented LCA processes. Totals will be generated for each area, then weighted and added to arrive at an overall score. Four groups of weightings will be used based on the vehicle type: small cars, mid-size cars, large/luxury cars, and trucks.

As the computer efficiency and capability increase, so as the Computer Aided Engineering (CAE) technologies improve. Recently Robust Design or Reliability Based Design Optimization (RBDO) technologies have been utilized in all sorts of industries including automotive. The process generally involves identifying key input design variables and key performance output variables, determining a sampling plan for CAE simulations, building a response surface model (RSM), analyzing the results, and finding the optimized design that meets the reliability criteria. Yet little was addressed on the robustness of a CAE design model in the process. A systematic method of defining Robustness in a CAE design model was developed. How robust a CAE model is and how far away an optimized design is from the More Robust Region (MRR) are addressed in this paper.

This paper discusses the recent growth in aluminum wheel popularity and the problems associated with maintaining the wheel's appearance and corrosion protection. The various options in wheel coatings are then described as well as the adverse wheel environment. Finally, the variables affecting wheel corrosion resistance are explained and the testing that is undertaken to evaluate the performance characteristics of the wheel coating.

Loss of power steering assist (LoA) is viewed as a potential hazard in certain vehicle operational scenarios. Despite the importance of this steering failure mode, few published test protocols for the objective or subjective evaluation of vehicle performance in a loss of assist situation exist. The first part of this paper examines five of the key steering failure modes that can result in LoA and discusses why LoA persists as a key industry challenge. The second part analyzes the situational dynamics affecting vehicle controllability during a LoA event and proposes a subjective evaluation driving course that facilitates evaluations in various LoA scenarios. A corresponding objective test procedure and metric is also proposed. These evaluation methods support consistent performance evaluation of physical vehicles while also enabling the prediction of vehicle characteristics early in the vehicle development process (VDP).

The main objective of this paper is to simulate the springback using combined kinematic/isotropic hardening model. Material parameters in the hardening model are identified by an inverse method. Three-point bending test is conducted on 6022-T4 aluminum sheet. Punch stroke, punch load, bending strain and bending angle are measured directly during the tests. Bending moments are then computed from these measured data. Bending moments are also calculated based on a constitutive model. Material parameters are identified by minimizing the normalized error between two bending moments. Micro genetic algorithm is used in the optimization procedure. Stress-strain curves is generated with the material parameters found in this way, which can be used with other plastic models. ABAQUS/Standard 5.8, which has the combined isotropic/kinematic hardening model, is used to simulate draw-bend of 6022-T4 series aluminum sheet. Absolute springback angles are predicted very accurately.

This paper describes the validation of RAMSIS, a 3-D CAD human model for ergonomic vehicle evaluation. At GM NAO, the model’s capability to correctly predict position and posture in vehicle CAD environments was tested. H- and Eye point locations between RAMSIS manikins and their human counterparts were compared. At GM/SAAB the model’s postural discomfort predictability was evaluated. Changes in postural discomfort predictions of the RAMSIS manikins were compared to that of the human subjects when they evaluated two different driving buck conditions. We concluded that RAMSIS has good position, posture and postural discomfort prediction capabilities and is a useful CAD ergonomic evaluation and design tool for vehicle interiors.