Search Results

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.

Fatigue behaviors of aluminum 5754-O spot friction welds made by a concave tool in lap-shear specimens are investigated based on experimental observations and a fatigue life estimation model. Optical micrographs of the welds before and after failure under quasi-static and cyclic loading conditions are examined. The micrographs indicate that the failure modes of the 5754 spot friction welds under quasi-static and cyclic loading conditions are quite different. The dominant kinked fatigue cracks for the final failures of the welds under cyclic loading conditions are identified. Based on the experimental observations of the paths of the dominant kinked fatigue cracks, a fatigue life estimation model based on the stress intensity factor solutions for finite kinked cracks is adopted to estimate the fatigue lives of the welds.

In this investigation, dissimilar 5754/7075 and 7075/5754 spot friction welds were first made under different processing conditions. The spot friction welds in lap-shear specimens were tested under quasi-static loading conditions. The optimal processing times to maximize the failure loads of the 5754/7075 and 7075/5754 welds under lap-shear loading conditions are identified. The maximum failure load of the 7075/5754 welds is about 40% larger than that of the 5754/7075 welds. Optical micrographs of both types of spot friction welds made at different processing times before and after failure are examined. The micrographs show different weld geometries and different failure modes of spot friction welds made at different processing times. The failure modes of the 5754/7075 and 7075/5754 spot friction welds appear to be quite complex and strongly depend on the geometry and the strength of the interfacial surface between the two deformed sheet materials.

Two alternative finite element formulations are described which consider the influence of normal stress components on sheet deformations in Quick Plastic Forming [1]. The new formulations, single field bricks and multi-field shells, were implemented in the forming simulation program PAM-STAMP [2] using a non-linear viscoelastic constitutive relation [3,4]. Simulations of two industrial components indicate that both new elements simulate local necking more accurately than the standard shells which ignore normal stresses. The multi-field shells require slightly more calculation time than the standard shells and significantly less than equivalent brick models.

A summary of the design and development process for a Formula SAE engine is described. The focus is on three fundamental elements on which the entire engine package is based. The first is engine layout and displacement, second is the fuel type, and third is the air induction method. These decisions lead to a design around a 4-cylinder 600cc motorcycle engine, utilizing a turbocharger and ethanol E-85 fuel. Concerns and constraints involved with vehicle integration are also highlighted. The final design was then tested on an engine dynamometer, and finally in the 2007 M-Racing FSAE racecar.

Adopting robust design principles is a proven methodology for increasing design reliability. General Motors Powertrain (GMPT) has incorporated robust design principles into their Signal Delivery Subsystem (SDSS) development process by moving traditional prototype manufacturing and test functions from hardware to software. This virtual manufacturing technique, where subsystems are built and tested using simulation software, increases the number of possible prototype iterations while simultaneously decreasing the time required to gather statistically meaningful test results. This paper describes how virtual manufacturing was developed using distributed computing.

A unified approach to collision warning due to in-lane and neighboring traffic is presented. It is based on the concept of velocity obstacles, and is designed to alert the driver of a potential front collision and against attempting a dangerous lane change maneuver. The velocity obstacle represents the set of the host velocities that would result in collision with the respective static or moving vehicle. Potential collisions are simply determined when the velocity vector of the host vehicle penetrates the velocity obstacle of a neighboring vehicle. The generality of the velocity obstacle and its simplicity make it an attractive alternative to competing warning algorithms, and a powerful tool for generating collision avoidance maneuvers. The velocity obstacle-based warning algorithm was successfully tested in simulations using real sensor data collected during the Automotive Collision Avoidance System Field Operational Test (ACAS FOT) [10].

This paper illustrates a methodology in which complete material-manufacturing process cases for closure panels, reinforcements, and assembly are modeled and compared in order to identify the preferred option for a lightweight closure design. First, process-based cost models are used to predict the cost of lightweighting the closure set of a sample midsized sports utility vehicle (SUV) via material and process substitution. Weight savings are then analyzed using a powertrain simulation to understand the impact of lightweighting on fuel economy. The results are evaluated in the context of production volume and total mass change.

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.

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.

While the industry has recognized the value of modeling and code generation, the role of verification has taken a limited second tier role. Model Based Testing (MBT) is typically discussed in the context of automation of testing activities to eliminate the burden of generation and execution of tests. Unfortunately, this objective of effort minimization has skewed solutions away from using quality as a guiding metric. Alternatively, we have identified the simple objective of increasing the quality of testing practices and productivity of developers. In the following paper we introduce the integration of traditional software quality practices of functional, unit, and regression testing with the automated, model-driven world. This approach enables a quantitative approach to model driven software quality. The result is a robust technique that enables confident use of model-based development for production applications.

The drum brake pulsation is an issue that may cause a major customer complaint. One of the root causes of the drum pulsation is the deformation of the drum to an out of roundness (OOR) shape during the wheel-drum-axle assembly process under the presence of the uneven wheel flatness. This paper summarizes the newly developed OOR simulation method using ABAQUS and the counter-measures to reduce the OOR, and subsequently pulsation, by identifying the drum design parameter effects on OOR.

The effects of strain-rate and element mesh size on the numerical simulation of an automotive component impacted by a mass dropped from an instrumented drop tower was investigated. For this study, an analysis of a simple steel rail hat-section impacted by a mass moving at an initial velocity of 28Mph was performed using the explicit finite element code Radioss. Three constitutive material models: Elasto-Plastic (without strain rate), Johnson-Cook, and Zerilli-Armstrong were used to characterize the material properties for mild and high strength steel. Results obtained from the numerical analyses were compared to the experimental data for the maximum crush, final deformation shape, average crush force and the force-deflection curve. The results from this study indicate that the mechanical response of steel can be captured utilizing a constitutive material model which accounts for strain rate effect coupled with an average mesh size of 6 to 9mm.

This study involves an application of Principal Component Analysis (PCA) conducted in support of a Design for Six Sigma (DFSS) project. Primary focus of the project is to optimize seat parameters that influence Low Speed Rear Impact (LSRI) whiplash performance. During the DFSS study, the project team identified a need to rank order critical design factors statistically and establish their contribution to LSRI performance. It is also required to develop a transfer function for the LSRI rating in terms of test response parameters that can be used for optimization. This statistical approach resulted in a reliable transfer function that can applied across all seat designs and enabled us to separate vital few parameters from several many.

By adapting vehicle control systems to the skill level of the driver, the overall vehicle active safety provided to the driver can be further enhanced for the existing active vehicle controls, such as ABS, Traction Control, Vehicle Stability Enhancement Systems. As a follow-up to the feasibility study in [1], this paper provides some recent results on data-driven driving skill characterization. In particular, the paper presents an enhancement of discriminant features, the comparison of three different learning algorithms for recognizer design, and the performance enhancement with decision fusion. The paper concludes with the discussions of the experimental results and some of the future work.

Model-based design is a collection of practices in which a system model is at the center of the development process, from requirements definition and system design to implementation and testing. This approach provides a number of benefits such as reducing development time and cost, improving product quality, and generating a more reliable final product through the use of computer models for system verification and testing. Model-based design is particularly useful in automotive control applications where ease of calibration and reliability are critical parameters. A novel application of the model-based design approach is demonstrated by The Ohio State University (OSU) student team as part of the Challenge X advanced vehicle development competition. In 2008, the team participated in the final year of the competition with a highly refined hybrid-electric vehicle (HEV) that uses a through-the-road parallel architecture.

We start our study with a survey of existing variable valve actuation (VVA) devices. We then describe our work, taken place over a time period from 2001 to 2007, on several VVA concepts. All of our projects described include pre-design modeling and simulation. Also, for each one of the proposed designs, a bench-top motorized test fixture was built and ran for proof of concept. Our projects represent a mixture of exploratory research and production-related development work. They can be classified in four broad categories: discrete-step systems; mechanical continuously-variable systems; active stationary-hydraulic lash adjusters; cam-driven hydraulic-lost-motion mechanism. These devices differ in their complexity and versatility but offer a spectrum of design solutions applicable to a range of products. Specific attributes of these different approaches are analyzed and discussed, and some test results are presented.

The Advanced Engineering (AE) group within General Motors Powertrain (GMPT) develops next generation engines and transmissions for automotive and marine products. As a research organization, AE needs to prototype design ideas quickly and inexpensively. To this end, AE has embraced model-based development techniques and is currently investigating the benefits of software in-the-loop (SIL) testing. The underlying obstacle faced in developing a practical SIL system lays in the ability to integrate a plant model with sufficient fidelity together with target application software. ChiasTek worked with AE utilizing their CosiMate tool chain to eliminate these barriers and delivered a flexible SIL system simulation solution.

This paper demonstrates the benefit of using simulation and robust optimization for the problem of balancing vehicle noise, vibration, and ride performance over road impacts. The psychophysics associated with perception of vehicle performance on an impact is complex because the occupants encounter both tactile and audible stimuli. Tactile impact vibration has multiple dimensions, such as impact hardness and memory shake. Audible impact sound also affects occupant perception of the vehicle quality. This paper uses multiple approaches to produce the similar, robust, optimized tuning strategies for impact performance. A Design for Six Sigma (DFSS) project was established to help identify a balanced, optimized solution. The CAE simulations were combined with software tools such as iSIGHT and internally developed Kriging software to identify response surfaces and find optimal tuning.

In this article, the authors illustrate the benefits of axiomatic design (AD) for robust optimization and how to integrate axiomatic design into a total robust design process. Similar to traditional robust design, the purpose of axiomatic design is to improve the probability of a design in meeting its functional targets at early concept generation stage. However, axiomatic design is not a standalone method or tool and it needs to be integrated with other tools to be effective in a total robust development process. A total robust development process includes: system design, parameter design, tolerance design, and tolerance specifications [1]. The authors developed a step-by-step procedure for axiomatic design practices in industrial applications for consistent and efficient deliverables. The authors also integrated axiomatic design with the CAD/CAE/statistical/visualization tools and methods to enhance the efficiency of a total robust development process.