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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.

Once the design of a door sheetmetal and accessories is confirmed, the acoustics of the door system depends on the sound package assembly. This essentially consists of a watershield which acts as a barrier and a porous material which acts as an absorber. The acoustical performance of the watershield and the reverberant sound build-up in the door cavity control the performance. This paper discusses the findings of a design study that was developed based on design of experiments (DOE) concepts to determine which parameters of the door sound package assembly are important to the door acoustics. The study was based on conducting a minimum number of tests on a five factor - two level design that covered over 16 different design configurations. In addition, other measurements were made that aided in developing a SEA model which is also compared with the findings of the results of the design study.

Laser lap welding quality is a non-linear response based on a host of categorical and numeric material and process variables. This paper describes a Grammatical Evolution approach to the structure identification of the laser lap welding process and compares its performance with linear regression and a neuro-fuzzy inference system.

This paper reports on DaimlerChrysler's participation in the Ad Hoc Diesel Fuels Test Program. This program was initiated by the U.S. Department of Energy and included major U.S. auto makers, major U.S. oil companies, and the Department of Energy. The purpose of this program was to identify diesel fuels and fuel properties that could facilitate the successful use of compression ignition engines in passenger cars and light-duty trucks in the United States at Tier 2 and LEV II tailpipe emissions standards. This portion of the program focused on minimizing engine-out particulates and NOx by using selected fuels, (not a matrix of fuel properties,) in steady state dynamometer tests on a modern, direct injection, common rail diesel engine.

This paper deals with the multi-parameter and boundary mannequin techniques in creating human models in automotive applications. The concepts and applications of single-parameter, multiple parameter and boundary mannequin method are discussed respectively to clarify certain confusion. Emphasis is put on how to create boundary mannequins for a specific application, which may have been puzzling many engineers in practical applications. The authors would like to share their experience in using the digital human modeling software and make discussions on some common issues. A number of case studies from typical automotive manufacturing assembly operations are also presented to demonstrate the usage of the multi-parameter and boundary mannequin techniques.

Conventional car manufacturing is extremely capital and energy-intensive. Due to these limitations, major auto manufacturers produce very similar, if not virtually identical, vehicles at very large volumes. This limits potential customization for different users and acts as a barrier to entry for new companies or production techniques. Better understanding of the barriers for low volume production and possible solutions with innovative production techniques is crucial for making low volume vehicles viable and accelerating the adoption of new production techniques and lightweight materials into the competitive marketplace. Additive manufacturing can enable innovative design with minimal capital investment in tooling and hence should be ideal for low and perhaps high volume parts. For this reason, it was desired to evaluate potential opportunities in manufacturing automotive parts with additive techniques.

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.

The Automotive Industry/Government Emissions Research CRADA (AIGER) has been working to develop a new methodology for the direct determination of nonmethane hydrocarbons (DNMHC) in vehicle testing. This new measurement technique avoids the need for subtraction of a separately determined methane value from the total hydrocarbon measurement as is presently required by the Code of Federal Regulations. This paper will cover the historical aspects of the development program, which was initiated in 1993 and concluded in 2002. A fast, gas chromatographic (GC) column technology was selected and developed for the measurement of the nonmethane hydrocarbons directly, without any interference or correction being caused by the co-presence of sample methane. This new methodology chromatographically separates the methane from the nonmethane hydrocarbons, and then measures both the methane and the backflushed, total nonmethane hydrocarbons using standard flame ionization detection (FID).

The Ethanol-Boosted Direct Injection (EBDI) demonstrator engine is a collaborative project led by Ricardo targeted at reducing the fuel consumption of a spark-ignited engine. This paper describes the design challenges to upgrade an existing engine architecture and the synergistic use of a combination of technologies that allows a significant reduction in fuel consumption and CO₂ emissions. Features include an extremely reduced displacement for the target vehicle, 180 bar cylinder pressure capability, cooled exhaust gas recirculation, advanced boosting concepts and direct injection. Precise harmonization of these individual technologies and control algorithms provide optimized operation on gasoline of varying octane and ethanol content.

With the adoption of the California Low-Emission Vehicle Regulations and the associated lower emission standards such as LEV (Low-Emission Vehicle in 1990), ULEV (Ultra-Low-Emission Vehicle), and LEV II (1998 with SULEV-Super Ultra Low Emission Vehicle), concerns were raised by emissions researchers over the accuracy and reliability of collecting and analyzing emissions measurements at such low levels. The primary concerns were water condensation, optimizing dilution ratios, and elimination of background contamination. These concerns prompted a multi-year research program looking at several new sampling techniques. This paper will describe the cooperative research conducted into one of these new technologies, namely the Bag Mini-Diluter (BMD) and Direct Vehicle Exhaust (DVE) Volume system.

A finite element methodology, based on implicit numerical integration procedure, for simulating oil-canning tests on Door assemblies is presented. The method takes into account nonlinearities due to geometry, material and contact between parts during deformation. The simulation results are compared with experimental observations. Excellent correlation between experimental observations and analytical predictions are obtained in these tests. Armed with the confidence in the methodology, simulations on a door assembly are conducted to study the gage and grade sensitivities of the outer panel. The sensitivity studies are conducted on three different grades of steel for the outer panel. Further studies are conducted to understand the effects of manufacturing (forming operation) on the oil canning behavior of door assembly. Results demonstrate the utility of the method in material selection during pre-program design of automotive structures.

The problem of predicting the quality of weld is critical to manufacturing. A great deal of data is collected under multiple conditions to predict the quality. The data generated at Daimler Chrysler has been used to develop a model based on grammatical evolution. Grammatical Evolution Technique is based on Genetic Algorithms and generates rules from the data which fit the data. This paper describes the development of a software tool that enables the user to choose input variables such as the metal types of top and bottom layers and their thickness, intensity and speed of laser beam, to generate a three dimensional map showing weld quality. A 3D weld quality surface can be generated in response to any of the two input variables picked from the set of defining input parameters. This tool will enable the user to pick the right set of input conditions to get an optimal weld quality. The tool is developed in Matlab with Graphical User Interface for the ease of operation.

OEMs are investigating opportunities to reduce vehicle mass, driven by a need to meet upcoming CAFE targets, increase the range and reduce battery size of EVs. A number of lightweight materials including high strength steels, aluminum alloys, plastics and composites are now in production. To facilitate development of corporate R&D and commercialization plans for new materials, it is beneficial to understand the current manufacturing costs for production components, and their impact on piece price at different volumes. This paper investigates design and cost impact of light-weighting with respect to front door and floor assembly of Toyota Corolla and BMW i3. Toyota Corolla has a traditional steel body and is sold in high volumes while BMW i3 has relatively low annual sales and is primarily made of composite, aluminum and plastic parts.

A new multi-layer co-extruded in-color Ionomer film is developed to provide an alternative decoration process to replace paint on Dodge Neon Fascias. The Ionomer film provides a high-gloss “class-A” surface in both non-metallic and metallic colors that match the car body paint finish. Using the Ionomer film to decorate fascias reduces cost; eliminates VOCs; increases manufacturing flexibility and improves performance (weatherability and durability). The molding process consists of thermoforming a film blank and injection molding Polypropylene or TPO behind the film. The paper will include the background, the benefits, the technology development objectives, the film materials development, tooling optimization, film fascia processing (co-extrusion; thermoforming and injection molding) and validation testing of the film.

Laminated steel sheets sandwiched with a polymer core are increasingly used for automotive applications due to their vibration and sound damping properties. However, it has become a major challenge in finite element modeling of laminated steel structures and forming processes due to the extremely large differences in mechanical properties and in the gauges of the polymer core and the steel skins. In this study, circular cup deep drawing and V-bending experiments using laminated steels were conducted in order to develop a modeling technique for laminate forming processes. The effectiveness of several finite element modeling techniques was investigated using the commercial FEM code LS-Dyna. Furthermore, two production parts were selected to verify the modeling techniques in real world applications.

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.

It is commonly known that in an automotive manufacturing assembly line several workers perform either a common task or a number of different tasks simultaneously, and there is a need to represent such a multi-worker operation realistically in a digital environment. In the past years, most digital human modeling applications were limited only in a single worker case. This paper presents how to simulate multi-worker operations in a digital workcell. To establish an effective communication and interaction between the mannequins, some existing commercial software package has provided a digital input/output mechanism. The motion for each mannequin is often programmed independently, but can be interrupted anytime by the other digital human models or devices via a communication channel.

In response to environmental and fossil fuel usage concerns, the automotive industry will gradually move from Hybrid Electric Vehicles (HEV) which includes a shift of internal combustion engines toward Zero Emissions Vehicles (ZEV). Refinement is an important aspect in the successful adoption of any new technology and ZEV brings its own NVH challenges owing to the unique dynamic characteristics of the powertrain and driveline system. This paper presents considerations for addressing dynamic driveline NVH issues that are common to 100% electric vehicles; issues that manifest themselves as groans, rattles and clunks. A dynamic torsional analytical model of the powertrain & driveline will be presented. The analytical model served as the baseline for an extensive parametric study using the Genetic Algorithm (GA) technique, whereby the effectiveness of practical countermeasures was investigated.

As SULEV emission regulations approach, the bag mini-diluter (BMD) technology is gaining acceptance as a replacement for the existing constant volume sampler (CVS) for SULEV exhaust emission measurement and certification. The heart of the BMD system is the direct vehicle exhaust (DVE) flow measurement system. Due to the transient nature of vehicle exhaust during a standard FTP emission test cycle, the DVE must be capable of rapid and accurate response in order to track these varying exhaust flow rates. The DVE must also be robust enough to accurately measure flow rate despite variations in exhaust gas composition, pulsation effects, and rapid changes in both exhaust temperature and pressure. One of the primary DVE systems used on BMDs is the E-Flow, an ultrasonic flow meter manufactured by Flow Technologies, Inc.

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.