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This paper presents a 2D model for frontal vehicle-to-vehicle crashes that can be used for fleet modeling. It presents the derivational details and a preliminary assessment of the model. The model is based on rigid-body collision principles, enhanced adequately to represent energy dissipation and lateral engagement that plays a significant role in oblique frontal vehicle-to-vehicle crashes. The model employs the restitution and the apparent friction in order to represent dissipation and engagement respectively. It employs the impulse ellipse to identify the physical character of the crash, based on the principal directions of impulse. The enhancement of the rigid body collision model with restitution and apparent friction is based on collision simulations that use very simple finite element vehicle representations. The dependence of the restitution and the apparent friction on the incidence angle, the frontal offset, and the mass ratio, as predicted by the 2D model, has been presented.

One of the primary reasons that FMVSS 111 currently requires flat rearview mirrors as original equipment on the driver's side of passenger cars is a concern that convex mirrors might reduce safety by causing drivers to overestimate the distances to following vehicles. Several previous studies of the effects of convex rearview mirrors have indicated that they do cause overestimations of distance, but of much lower magnitude than would be expected based on the mirrors' levels of image minification and the resulting visual angles experienced by drivers. Previous studies have investigated mirrors with radiuses of curvature up to 2000 mm. The present empirical study was designed to investigate the effects of mirrors with larger radiuses (up to 8900 mm). Such results are of interest because of the possible use of large radiuses in some aspheric mirror designs, and because of the information they provide about the basic mechanisms by which convex mirrors affect distance perception.

A finite element model of the Transport Research Laboratory (TRL) honeycomb barrier, which is being proposed for use in vehicle compatibility studies, has been developed for use in LSDYNA. The model employs penalty parameters to enforce continuity between adjacent finite elements of the honeycomb barrier. Results of impact tests with indentors of various shapes and sizes were used to verify the performance of the computational model. Numerical simulations show reasonably good agreement with the test results.

Combustion flame geometry calculation is a critical task in the design and analysis of combustion engine chamber. Combustion flame directly influences the fuel economy, engine performance and efficiency. Currently, many of the flame geometry calculation methods assume certain specific chamber and piston top shapes and make some approximations to them. Even further, most methods can not handle multiple spark plug set-ups. Consequently, most of the current flame geometry calculation methods do not give accurate results and have some built-in limitations. They are particularly poor for adapting to any kind of new chamber geometry and spark plug set-up design. This report presents a novel methodology which allows the accurate calculation of flame geometry regardless of the chamber geometry and the number of spark plugs. In this methodology, solid models are used to represent the components within the chamber and unique attributes (colors) are attached respectively to these components.

A hybrid Finite Element Analysis (hybrid FEA) formulation has been developed in the past for computing the mid-frequency vibration of systems that contain one type of energy. The hybrid FEA is based on characterizing as long members in a system all the members that contain a large number of wavelengths within their dimension. All the remaining members are considered as short. The Energy Finite Element Analysis (EFEA) is employed for modeling the behavior of the long members, while the conventional FEA method is utilized for modeling the short members. In this paper the hybrid FEA formulation is extended to plate structures that are spot-welded to a frame comprised by tubular members. The new formulation is validated by comparing the hybrid FEA solution to results produced by very dense conventional FEA models in the mid-frequency range.

A new development in the area of the hybrid Finite Element Analysis (hybrid FEA) is presented. The hybrid FEA method combines the conventional FEA method with energy FEA (EFEA) for analysis of systems that contain both flexible and stiff members, and is suitable for mid-frequency computations. A formulation for analyzing flexible plates spot-welded to stiff beams when the excitation is applied on the stiff members is developed. Conventional FEA models are employed for modeling the behavior of the stiff members in a system. Appropriate damping elements are introduced in the connections between stiff and flexible members in order to capture the presence of the flexible members during the analyses of the stiff ones.

Current automotive design practices related to driver visibility are based on static laboratory studies of mostly straight ahead viewing that were conducted by Meldrum and others beginning in 1962. These individual studies have never been replicated either in the lab or in actual driving situations to determine the validity of their procedures. After a thorough review of the literature related to driver eye location and a statistical analysis of previous static eye location data, an experimental design is proposed to determine dynamic eye location distribution characteristics. This design will provide information on: (a) the relationship of static anthropometric measurements to dynamic eye location; (b) the difference between dynamic on-the-road eye location versus static in-the-lab eye location distributions: (c) the effect of different types of vehicle seating package parameters on eye location; and, (d) a validation of previous static eye location studies.

Stochastic simulation is used to account for the uncertainties inherent to the system and enables the study of crash phenomenon. For analytical purposes, random variables such as material crash properties, angle of impact, human response and the like can be characterized using statistical models. The methodology outlined in this approach is based on using the information about the probability of random variables along with structural behavior in order to quantify the scatter in the structural response. Thus the analysis gives a more complete picture of the actual simulation. Practical examples for the use of this technique are demonstrated and an overview of this approach is presented.

The use of commercial finite element analysis (FEA) software to perform stamping feasibility studies of automotive components has grown extensively over the last decade. Although product and process engineers have now come to rely heavily on results from FEA simulation for manufacturability of components, the prediction of springback has still not been perfected. Springback prediction for simple geometries is found to be quite accurate while springback prediction in complex components fails to compare with experimental results. Since most forming simulation FEA software uses a dynamic explicit solution method, the choice of various input parameters greatly affects the prediction of post formed stresses in the final component. Accurate stress prediction is critical for determination of springback, therefore this study focuses on the effects of some of the simulation parameters such as, element size, tool/loading speed and loading profile.

A formulation that accounts for manufacturing variability in the analysis of structural/acoustic systems is presented. The methodology incorporates the concept of fast probability integration with finite element (FEA) and boundary element analysis (BEA) for producing the probabilistic acoustic response of a structural/acoustic system. The advanced mean value method is used for integrating the system probability density function. FEA and BEA are combined for producing the acoustic response that constitutes the performance function. The probabilistic acoustic response is calculated in terms of a cumulative distribution function. The new methodology is used to illustrate the difference between the results from a probabilistic analysis that accounts for manufacturing uncertainty, and an equivalent deterministic simulation through applications. The probabilistic computations are validated by comparison to Monte Carlo simulations.

Reductions of hardware costs as well as implementations of new innovative functions are the main drivers of today's automotive electronics. Indeed more and more resources are spent on adapting existing solutions to different environments. At the same time, due to the increasing number of networked components, a level of complexity has been reached which is difficult to handle using traditional development processes. The automotive industry addresses this problem through a paradigm shift from a hardware-, component-driven to a requirement- and function-driven development process, and a stringent standardization of infrastructure elements. One central standardization initiative is the AUTomotive Open System ARchitecture (AUTOSAR). AUTOSAR was founded in 2003 by major OEMs and Tier1 suppliers and now includes a large number of automotive, electronics, semiconductor, hard- and software companies.

The feature of offered algorithm is that it allows, without record and analysis of the display diagram, to estimate a running cycle of a diesel engine parameters which characterize ecological and economic performances. The mathematical model described in report allows to determine connection of coefficient of filling, pressure and temperature of air boost, factor of excess of air with effectiveness ratio of combustion and contents of soot in exhaust gas and to take into account this connection at a choice initial data for control fuel feed or for elaboration of diesel engine dynamic model. The algorithm incorporated, for example, in the microcontroller of an electronic fuel feed controller allows analyzing the sensors data and theoretically determine of smoke amount in the exhaust gases for chosen cycle of fuel feed. The restriction of smoke is possible by criterion dD/dGT, where D - contents of soot in exhaust gas and GT - fuel cycle submission under the program-adaptive schema.

In the I-bumper (inflatable bumper) concept [1], two explosive airbags are released just before the main body-to-body crash in order to absorb the kinetic energy of colliding vehicles. The release also actuates other components in the I-bumper, including a movable bumper and an energy absorption morphing lattice structure. A small explosive charge will be used to deploy the airbag. A conventional airbag model will be used to reduce the crash energy in a controlled manner and reduce the peak impact force. An analytic model of the explosive airbag is developed in this paper for the I-bumper system and for its optimal design, while the complete system design (I-bumper) will be discussed in a separate paper. Analytical formulations for an explosive airbag will be developed and major design variables will be identified. These are used to determine the required amount of explosive and predict airbag behavior, as well to predict their impact on the I-bumper system.

The greatest demand facing the automotive industry has been to provide safer vehicles with high fuel efficiency at minimum cost. Current automotive vehicle structures have one fundamental handicap: a short crumple zone for crash energy absorption. This leaves limited room for further safety improvement, especially for high-speed crashes. Breakthrough technologies are needed. One potential breakthrough is to use active devices instead of conventional passive devices. An innovative inflatable bumper concept [1], called the “I-bumper,” is being developed by the authors for crashworthiness and safety of military and commercial vehicles. The proposed I-bumper has several active structural components, including a morphing mechanism, a movable bumper, two explosive airbags, and a morphing lattice structure with a locking mechanism that provides desired rigidity and energy absorption capability during a vehicular crash.

Automotive exhaust emission regulations are becoming progressively stricter due to increasing awareness of the hazardous effects of exhaust emissions. The main challenge to meet the regulations is to reduce the emissions during cold starts, because catalytic converters are ineffective until they reach a light-off temperature. It has been found that 50% to 80% of the regulated hydrocarbon and carbon monoxide emissions are emitted from the automotive tailpipe during the cold starts. Therefore, understanding the catalytic converter characteristics during the cold starts is important for the improvement of the cold start performances This paper describes a mathematical model that simulates transient performances of catalytic converters. The model considers the effect of heat transfer and catalyst chemical reactions as exhaust gases flow through the catalyst. The heat transfer model includes the heat loss by conduction and convection.

A hybrid finite element formulation for analyzing flexible plates connected to stiff frame was developed. The excitation was considered to be applied on the stiff members. Conventional FEA models were employed for modeling the behavior of the stiff members in a system. Appropriate damping elements were introduced in the connections between stiff and flexible members in order to capture the presence of the flexible members during the analyses of the stiff ones. Once the vibration of the stiff members and the amount of power dissipated at the damping elements was identified, an EFEA analysis was performed in order to determine the amount of vibrational energy in the flexible members. The hybrid FEA is applied to a Body-In-White (BIW). The results of the hybrid FEA are compared with results from very dense conventional finite element analyses.

This paper describes the approximation of the engine torque of an SI-engine using recurrent neural networks. As modern engine control units today are based on engine torque management, there is a need for an accurate determination of the produced engine torque. Since direct measurements of this value are not possible in series applications due to resulting high costs, a fast and accurate algorithm for the approximation of these values from other sensor signals has to be found. Dynamic neural networks are a promising method to fulfill these requirements.

Mathematical models of the automotive system play a valuable role in forecasting and policy analysis, especially in the public sector. However, poor documentation, lack of adequate model evaluation and unfamiliarity with the data and structural limitations of models suggest the possibility of misuse in such policy applications as fuel economy standards and regulatory impact assessments. Findings are illustrated by analysis of two models: the Wharton EFA Automobile Demand Model and the Sweeney Passenger Car Gasoline Demand Model. In addition, 40 world sector models and studies representing more than 75 countries are summarized.

Variable Valve Actuation (VVA) technology provides high potential in achieving high performance, low fuel consumption and pollutant reduction. However, more degrees of freedom impose a big challenge for engine characterization and calibration. In this study, a simulation based approach and optimization framework is proposed to optimize the setpoints of multiple independent control variables. Since solving an optimization problem typically requires hundreds of function evaluations, a direct use of the high-fidelity simulation tool leads to the unbearably long computational time. Hence, the Artificial Neural Networks (ANN) are trained with high-fidelity simulation results and used as surrogate models, representing engine's response to different control variable combinations with greatly reduced computational time. To demonstrate the proposed methodology, the cam-phasing strategy at Wide Open Throttle (WOT) is optimized for a dual-independent Variable Valve Timing (VVT) engine.

Future emission regulations and customer needs require revolutionary new approaches to engine management systems. In the EC part-funded AENEAS program the partners Ricardo, Kistler and DaimlerChrysler formed a consortium to investigate the application of a new combustion pressure sensor concept and innovative algorithms for engine management systems. This paper describes the general scope and the basic concepts of the system.