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One of the primary issues in the interpretation of vehicle impact response data, observed from vehicle crash test events, is coping with variability. This vehicle response inconsistency generally causes test results to be unpredictable and makes CAE test validation work difficult as well. This paper, considering the uncertain characteristics of vehicle impact events, has implemented a stochastic assessment of vehicle NCAP response variation through a CAE vehicle impact model, and it has accomplished the three primary study objectives as stated follows: 1) Identify the response variation causing factors stochastically from various structural and environmental factor candidates and quantify the degree of their influences on crash response, 2) Develop a methodology for interpreting the significance of the factor effects in conjunction with vehicle impact mechanics and physics, and 3) Implement a stochastic improvement of the vehicle NCAP responses and their repeatability

As part of an ongoing technical collaboration between Ford and Rouge Steel Company, a comprehensive study of door slam event was undertaken. The experimental phase of the project involved measurements of accelerations at eight locations on the outer panel and strains on six locations of the inner panel. Although slam tests were conducted with window up and window down, results of only one test is presented in this paper. The CAE phase of the project involved the development of suitable “math” model of the door assembly and analysis methodology to capture the dynamics of the event. The predictability of the CAE method is examined through detailed comparison of accelerations and strains. While excellent agreement between CAE and test results of accelerations on the outer panel is obtained, the analysis predicts higher strains on the inner panel than the test. In addition, the tendency of outer panel to elastically buckle is examined.

The objective of this work is to perform a computer model based sensitivity analysis of parameters of an automotive air conditioning system to identify the critical parameters. Design of Experiment (DOE) and Analysis of Variance (ANOVA) techniques have been used to identify the critical parameters and their relative effects on the air conditioning system performance. The sensitivity analysis has been verified by running similar tests on an air conditioning system test stand (AC Test Stand).

The durability of fuel tank straps is essential for vehicle safety. Extensive physical tests are conducted to verify designs for durability. Due to the complexity of the loads and the fuel-to-tank interaction, computer-aided-engineering (CAE) simulation has had limited application in this area. This paper presents a CAE method for fuel tank strap durability prediction. It discusses the analytical loads, modeling of fuel-to-tank interaction, dynamic analysis methods, and fatigue analysis methods. Analysis results are compared to physical test results. This method can be used in either a fuel-tank-system model or a full vehicle model. It can give directional design guidance for fuel tank strap durability in the early stages of product development to reduce vehicle development costs.

Computer applications have been widely used to assist product design. The successes and sophistication of computer aided engineering (CAE) techniques are respectfully recognized in this field. CAE applications in the manufacturing area however are still developing, although the manufacturing community is increasingly starting to pay attentions to computer simulations in its daily workings. This paper will briefly introduce some of these applications and promote awareness of computer simulations in manufacturing area. It contains four main sections: finite element analysis (FEA) in machining fixture design, FEA applications in component assembly, machining process simulations and machining vibrations in the milling operation. Each section comes with a practical case study, potential benefits are identified and conclusions are presented by using an integrated design and analysis approach.

Vehicle design and packaging is a repetitive and tedious process that involves frequent engineering and design changes. To improve design efficiency, a standard naming vehicle design methodology is proposed in this paper. For the geometric or the functional object used in the vehicle context, a standard name is assigned and also used as a unique object feature through its life cycle. With the proposed standard naming design methodology, the engineering knowledge can be efficiently embedded into the CAD design, and hence, vehicle design can be executed in a more automated fashion. Work case of the standard naming design methodology is illustrated by a vehicle design and packaging application using CATIA V5.

Rapid wear out of a disk brake due to phenomena commonly known as hot spots is one of various problems faced by brake manufacturers. Hot spots are localized high temperature areas generated on the frictional surface of a disk brake during braking. The non-uniform surface expansion caused by hot spots on the disk surface may cause pedal pulsation or known as thermal judder. This effect in the long run will shorten a brake's life. Numerical simulation of a disk brake requires the use of nonlinear contact mechanics approach. The simulation is computationally very expensive and difficult to perform. A computer simulation technique has been developed at the DaimlerChrysler Brake Core Group to investigate the hot spot phenomena since 1997. The technique was implemented on 3-D finite element models to simulate frictional contacts between the disk and its pads. Computer code ABAQUS is used for these analyses and computations are performed in Silicon Graphics, Origin 2000 machines.

Combustion feedback using cylinder pressure sensors, ion current sensors or alternative sensing techniques is actively under investigation by the automotive industry to meet future legislative emissions requirements. One of the drawbacks of many rapid prototyping engine management systems is their available analog interfaces, often limited to 10-12 bits with limited bandwidth, sampling rate and very simple anti-aliasing filters. Processing cylinder pressure or other combustion feedback sensors requires higher precision, wider bandwidths and more processing power than is typically available. For these reasons, Ricardo in collaboration with GM Research has developed a custom, high precision analog input subsystem for the rCube rapid prototyping control system that is specifically targeted at development of combustion feedback control systems.

Experimental and computational simulation techniques were concurrently employed throughout the aerodynamic development of the NASCAR Dodge Intrepid R/T in order to achieve a greater understanding of the complex flow fields involved. With less than 500 days to design, understand, and build a competitive vehicle, the development team utilized a closed loop approach to testing. Scale wind tunnel models and Computational Fluid Dynamics (CFD) were used to identify program direction and to speed the development cycle versus the traditional process of full scale testing. This paper will detail the process and application of both the experimental and computational techniques used in the aerodynamic development of the Intrepid R/T race vehicle, primarily focusing on the earlier stages that led to its competition introduction at the start of the 2001 season.

Exhaust durability is an important measure of quality, which can be predicted using CAE with accurate mount loads. This paper proposes an innovative method to calculate these loads from measured mount accelerations. A Chrysler vehicle was instrumented with accelerometers at both ends of its four exhaust mounts. The vehicle was tested at various durability routes or events at DaimlerChrysler Proving Grounds. These measured accelerations were integrated to obtain their velocities and displacements. The differences in velocities and displacements at each mount were multiplied by its damping and stiffness rates to obtain the mount load. The calculation was conducted for all three translational directions and for all events. The calculated mount loads are shown within reasonable range. Along with CAE, it is suggested to explore this method for exhaust durability development.

This paper describes a lightweight magnesium intensive automobile body structure concept developed at DaimlerChrysler to support a high fuel-efficiency vehicle project. This body structure resulted in more than 40% weight reduction over a conventional steel structure while achieving significantly improved structural performance as evaluated through CAE simulations. A business case analysis was conducted and showed promising results. One concept vehicle was built for the purpose of demonstrating concept feasibility. The paper also identifies areas for further development to enable such a vehicle to become a production reality at a later time.

In the early stages of a vehicle program, it is a common practice to set target ranges for the global body, suspension and powertrain modes. This modal management process allows engineers to avoid potential noise and vibration problems stemming from strong overlap of major global modes. Before the first prototype hardware is built, finite element models of the body, suspension and powertrain are usually exercised to compare predicted versus targeted ranges of the major system modes in the form of a modal management chart. However, uncertainty associated with the design parameters, manufacturing process and other sources can lead to a major departure from the design intent when the first hardware prototype is built. In this study, a first order reliability method is used to predict variance of the eigen values due to parameter uncertainties. This allows the CAE engineers to add a “three sigma” bound on the eigen values reported in the modal management chart.

During the design process for a vehicle, the CAD surface geometry becomes available at an early stage so that numerical assessment of aerodynamic performance may accompany the design of the vehicle's shape. Accurate prediction requires open grille models with detailed underhood and underbody geometry with a high level of detail on the upper body surface, such as moldings, trim and parting lines. These details are also needed for aeroacoustics simulations to compute wall-pressure fluctuations, and for thermal management simulations to compute underhood cooling, surface temperatures and heat exchanger effectiveness. This paper presents the results of a significant effort to capitalize on the investment required to build a detailed virtual model of a pickup truck in order to simultaneously assess performance factors for aerodynamics, aeroacoustics and thermal management.

In automotive industry, all passenger vehicles are treated with damping materials to reduce structure borne noise. The effectiveness of damping treatments depends upon design parameters such as choice of damping materials, locations and size of the treatment. This paper proposes a CAE (Computer Aided Engineering) methodology based on finite element analysis to optimize damping treatments. The developed method uses modal strain-energy information of bare structural panels to identify flexible regions, which in turn facilitates optimization of damping treatments with respect to location and size. The efficacy of the method is demonstrated by optimizing damping treatment for a full-size pick-up truck. Moreover, simulated road noise performances of the truck with and without damping treatments are compared, which show the benefits of applying damping treatment.

The automotive industry is rapidly implementing computer simulation in every aspect of their processes mainly to decrease the time required to bring new models to market. Computer simulation can also be used to reduce the cost of vehicle development and manufacturing. A major portion of the manufacturing cost associated with automotive stamping lies in the process design, build and tryout of production dies and in automation of the transfer equipment. Press home-line tryout is largely a trial-and-error process relying heavily on the skills and experience of tool and die makers. To reduce this dependence on human skills and effort, press-line simulation can be effectively utilized to verify the design accuracy thereby reducing the changes needed to rework the production die/tool. The entire press-line with all its complete accessories can be modeled and checked for design errors similar to the try-out conducted in the production plant.

A process to achieve vehicle system level NVH objectives using CAE simulation tools is discussed. Issues of modeling methodology, already covered adequately in the literature, are less emphasized so that the paper can focus on the application of a process that encompasses objective setting, design synthesis, and performance achievement using simulation predictions. A reference simulation model establishes correlation levels and modeling methods that are applied to future predictions. The new model, called a “Digital Mule”, is an early new product “design intent” simulation used to arrive at subsystem goals to meet the vehicle level NVH objectives. Subsystem goals are established at discrete noise paths where structure borne noise enters the body subsystem. The process also includes setting limits on the excitation sources, such as suspension and powertrain.

A newly-proposed hydroforming design of front rail was evaluated for product feasibility. Hydroforming and associated prebending and preforming processes were designed with the assistance of CAE tool. Optimized processing parameters were selected and the entire manufacturing process was simulated using FEA software. Potential manufacturing issues were identified and product modification was suggested accordingly.

Today automotive thermal systems development is a joint effort between an OEM and its suppliers. This paper presents a pilot program showing how OEMs and suppliers can jointly develop a reliable and robust thermal system using CAE tools over the internet. Federated Intelligent Product Environment (FIPER) has been used to establish B2B communication between OEMs and suppliers. Suppliers remotely run thermal systems computer models at the OEM site using the FIPER B2B feature.

The quality of engine lubrication depends upon how much oil is supplied and how the lubricant is pressurized to the lubricated components. These variables strongly affect the safe operation and lifespan of an engine. During the conceptual design stage of an engine, its lubrication system cannot be verified experimentally. It is highly desirable for design engineers to utilize computer simulations and robust design methodology in order to achieve their goal of optimizing the engine lubrication system. The heuristic design principle is a relatively routine resource for design engineers to pursue although it is time consuming and sacrifices valuable developing time. This paper introduces an unusual design methodology in which design engineers were involved in analyzing their own designs along with lubrication system analyst to establish a link between two sophisticated software packages.

Mechanical properties of as-rolled steels used in a vehicle vary with many parameters including gages, steel suppliers and manufacturing processes. The residual forming and strain rate effects of automotive components have been generally neglected in full vehicle crashworthiness analyses. Not having the above information has been considered as one of the reasons for the discrepancy between the results from computer simulation models and actual vehicle tests. The objective of this study is to choose the right material property for as-rolled steels for stamping and crash computer simulation, and investigate the effect of forming and strain rate on the results of full vehicle impact analyses. Major Body-in-White components which were in the crash load paths and whose material property would change in the forming process were selected in this study. The post-formed thickness and yield stress distributions on the components were estimated using One Step forming analyses.