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The battery support in a small car is an example of a subsystem that lends itself to mounted component dynamic fatigue analysis, due to its weight and localized attachments. This paper describes a durability analysis method that was developed to define the required enforced motion, stress response, and fatigue life for such subsystems. The method combines the large mass method with the modal transient formulation to determine the dynamic stress responses. The large mass method was selected over others for its ease of use and efficiency when working with the modal formulation and known accelerations from a single driving point. In this example, these known accelerations were obtained from the drive files of a 4-DOF shake table that was used for corresponding lab tests of a rear compartment body structure. These drive files, originally displacements, were differentiated twice and filtered to produce prescribed accelerations to the finite element model.

In developing the 2007 Model Year Saturn VUE Green Line hybrid vehicle, a vehicle model for prediction of fuel economy and performance was developed. This model was developed in Matlab / Simulink / Stateflow by augmenting an existing conventional vehicle model to include hybrid components and controls. The generic structure and the functionalities of the model are presented. This simulation model was used for rapid concept selection and requirements balancing early in the vehicle development process. Engine usage and energy distributions are shown based on simulation results. Fuel economy breakdown was also discussed.

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.

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.

The goal was to automate the entire analytical process of structural fatigue life variation assessment with respect to the variations associated with the geometry such as thickness, material properties and loading conditions. Consequently, the structural reliability is evaluated systematically. This process automation has been realized by using an internally developed software package called Structural Fatigue/Reliability Sensitivity II (i.e. FRS II). The package is a bundle of MSC/Nastran, nCode, iSIGHT, and internally developed program scripts.

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.

This paper discusses a standard procedure to reduce brake squeal using CAE and robust synthesis & analysis techniques. There are several techniques available to evaluate the stability of a system. Complex eigenvalue analysis is used for predicting and reducing squeal propensity. The complex eigenvalue method was implemented using SOL110 in version 2001 of MSC/NSTRAN for this study. We applied the signal to noise ratio using an orthogonal matrix to evaluate the main parameter effects and minimize the sensitivity.

This paper presents a project that was done to solve an integration problem between a brake system and a cruise control system on a GM vehicle program, each of which was supplied by a different supplier. This paper presents how the problem was resolved using a CAE tool which was a combination of formulated MS/Excel spreadsheet, Overdrive (GM internal code), and iSIGHT of Engineous Software Inc, which is a process integrator and process automator. A sensitivity study of system reliability was conducted using iSIGHT. The most sensitive factor was found through the sensitivity study. Thereafter, a Robust design was obtained. The recommended Robust Design was implemented in the vehicle program, which led to a substantial cost saving. The CAE software tool (the combination) developed through the problem solving process will be used to ensure quality of brake and cruise system performance for future vehicle programs.

Amendments to the Clean Air Act require the implementation of inspection/maintenance (I/M) programs in areas designated as non-attainment and unable to meet the National Ambient Air Quality Standards by 1982. Current I/M programs have been developed using data representative of pre- and early-catalyst emission control technology. Changes to current emission control systems and electronic computer controlled systems represent new emission control technology. This paper addresses the I/M situation as related to these system changes. Results of tests on a prototype system are presented. Parameter inspection and the utilization of built-in diagnostics on future systems have the potential to maximize the effectiveness of I/M programs.

This report describes the use of meshfree methods for response and design sensitivity calculations within structural reliability analysis when geometric shape is a random variable. Brief descriptions of meshfree methods and advanced probabilistic methods are provided. An existing interface between the probabilistic analysis and traditional finite element method is modified to allow the use of meshfree methods for response and design sensitivity calculations within the probabilistic analysis routine. Two examples that treat design shape as a random variable are presented to assess the accuracy and use of meshfree methods for reliability analysis.

In GM R&D Powertrain/Engine Control Group, rapid prototyping controller (RPC) systems with Matlab/Simulink are used extensively to design, simulate and implement advanced engine control algorithms and models. However, those RPC systems use powerful microprocessors with large amounts of RAM contrary to engine control modules (ECM) in production vehicles. Therefore, a thorough analysis on the comparatively much more complicated algorithms and models cannot be performed during the research stage, since there are not enough tools to enable the smooth transition from Matlab/Simulink to the production type processor. The Real-Time Interface (RTI) Blockset for a production like microprocessor would close the transition gap between rapid prototyping controller systems and production type microprocessors by leveraging the power and popularity of Matlab/Simulink in control engineering world and automatic code generation tools.

This paper describes the methodology used to design and perform a CFD analysis of a Chevrolet Impala SS Funny Car body. This body was designed for the purpose of making it available for teams to race it in the National Hot Rod Association (NHRA) drag racing series beginning with the 2007 race season. Several challenges were presented in this project: (1) This was the first time a General Motors drag racing body for use in professional classes (Funny Car or otherwise) was ever designed in CAD. (2) The body was originally designed as a 2007 Chevrolet Monte Carlo. After the tooling was completed, changes in Chevrolet’s product lineup required that the body be changed to a 2007 Impala SS. (3) Budget constraints precluded CFD analysis until after the bodies were already being manufactured. There were several teams that raced the new body during the 2007 race season. One of these teams won the Funny Car Driver’s Championship.

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.

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.

The stringent 1978 emission standards of 0.41 gm/mi HC, 3.4 gm/mile CO, and 0.4 gm/mi NOx may require the use of a dual catalytic converter system (reducing and oxidizing catalyst). These emission requirements have been achieved at low mileage with such a system, but it is complex and has exhibited poor durability. This system also results in the loss of fuel economy at the 1978 emission levels.

4-Post durability test simulations using a nonlinear FEA model have been executed by engineers responsible for structural durability performance and validation. An integrated Body and Chassis, full FEA model has been used. All components of the test load input were screened and only the most damaging events were incorporated in the simulation. These events included the Potholes, Belgian Block Tracks, Chatter Bump Stops, Twist Ditches, and Driveway Ramps. The CAE technology Virtual Proving Ground (eta/VPG®*) was used to model the full system and the 4-Post test fixtures. The nonlinear dynamic FE solver LS-DYNA** was used in this analysis. The fatigue damage of each selected event was calculated separately and then added together according to the test schedule. Due to the lack of stress/strain information from hardware test, only the analyzed fatigue damage results of the baseline model were scaled to correlate with physical test data.

In an endeavor to improve upon historically subjective and hardware-based steering tuning development, a team was formed to find an optimal and objective solution using Design For Six Sigma (DFSS). The goal was to determine the best valve assembly design within a hydraulic power-steering assist system to yield improved steering effort and feel robustness for all vehicle models in a future truck program. The methodology utilized was not only multifaceted with several Design of Experiments (DOEs), but also took advantage of a CAE-based approach leveraging modeling capabilities in ADAMS for simulating full-vehicle, On-Center Handling behavior. The team investigated thirteen control factors to determine which minimized a realistic, compounded noise strategy while also considering the ideal steering effort function (SEF) desired by the customer. In the end, it was found that response-dependent variability dominated the physics of our valve assembly design concept.

General Motors' vehicles are designed with an engine immobilizer theft deterrent system. An engine immobilizer theft deterrent system only allows starting of the vehicle engine after assuring the key is the correct key. The communication link from the vehicle to the key is a critical interface for the starting of the engine. This communication link must be reliable. The vehicle theft deterrent system's ability to communicate between the vehicle and transponder in the key is measured by the coupling factor. There are a number of physical interfaces that affect the coupling factor. The focus of this work is to understand the physics and critical design parameters involved in achieving optimal coupling factor to improve the first time quality in future designs. Achieving this objective will lead to designs robust to variances in material and packaging design and result in less testing. The process used in the past on these systems was the Design-Test-Fix approach.

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.

This paper outlines a newly developed method for predicting the coupled response of structures from their uncoupled forced responses without having to know the forces acting on such structures. It involves computing the forced response of originally uncoupled structures with several mass loadings at a potential coupling point. The response data obtained from such computations is then used to predict the coupled response. The theory for discrete linear systems is outlined in the paper and a numerical example is given to demonstrate the validity, advantages and limitations of the method. The method is primarily devised to obtain coupled response of linear dynamic systems from independent and uncoupled analytical simulations. Its application significantly decreases computation time by reducing the simulation model size and is excellent for “what if” scenarios where a large number of simulations would otherwise be necessary.