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General Motor's Corvette product engineering was given the challenge to find mass reduction opportunities on the painted body panels of the C6 Z06 through the utilization of carbon fiber reinforced composites (CFRC). The successful implementation of a carbon fiber hood on the 2004 C5 Commemorative Edition Z06 Corvette was the springboard for Corvette Team's appetite for a more extensive application of CFRC on the C6 Z06 model. Fenders were identified as the best application for the technology given their location on the front of the vehicle and the amount of mass saved. The C6 Z06 CFRC fenders provide 6kg reduction of vehicle mass as compared to the smaller RRIM fenders used on the Coupe and Convertible models.

This paper presents a comparison of methods for the identification of a reduced set of useful variables using a multidimensional system. The Mahalanobis-Taguchi System and a standard statistical technique are used reduce the dimensionality of vehicle ride based on consumer satisfaction ratings. The Mahalanobis-Taguchi System and cluster analysis are applied to vehicle ride. The research considers 67 vehicle data sets for the 6 vehicle ride parameters. This paper applies the Mahalanobis-Taguchi System to forecast consumer satisfaction and provides a comparison of results with those obtained from a standard statistical approach to the problem.

A technique which uses Finite Element Analysis (FEA) to derive important parameters involved in SEA (Statistical Energy Analysis) is discussed. Application of the method to a variety of structures has yielded good correlation with experimentally generated results. SEA parameters including Coupling Loss Factors (CLFs), modal densities, and subsystem equivalent masses were obtained. The technique has the advantage of incorporating structural detail to enhance SEA predictions at lower frequencies where global modes are important, and it can be applied early in the design phase since no hardware is required. With this study, SEA is more readily applied to structure-borne noise problems in vehicles.

Today's competitive market requires new products to have extremely high Quality; customer expectation demands it. Testing, Validation, Setting Requirements, Failure Mode & Effect Analysis (FMEA), and Design Reviews by themselves do not improve a product; they only provide information that has to be translated into Design/Manufacturing & Service tasks. The quality of these tasks determines how well the new product will perform at its introduction. This paper outlines a generic Development Process through the use of an automotive example for a Door Glass Guidance Mechanism. This process includes the fundamental steps involving recommendations for setting requirements, benchmarking, and a methodology on how to design in requirements through the use of analytical and experimental tools to create Robust Designs. Also included are examples of Validation and Assessment Plans that are requirement driven.

A method is presented to process random vibration data from a complete road durability test environment as stationary segments and then develop test profiles based on fatigue content of their power spectral densities. Background is provided on existing techniques for estimating fatigue damage in the frequency domain. A general model for stress response to acceleration is offered to address the vibration test's requirement for acceleration data and the fatigue prediction method's requirement for stress data. With these tools, the engineer can extend test correlation beyond failure modes to include retention of estimated fatigue damage. Recommendations allow for test time compression from editing and improve existing exaggeration methods.

This paper presents the fundamental principles of variation analysis and robust design for dimensional datum schemes. The kinematics equations for rigid body motions are simplified through linearization. The simplified formulations explicitly relate the dimensional deviations of a rigid part with its datum scheme configuration and dimensional variations at datum target points. This simplified approach can be used with either the first order Taylor series approximation or Monte Carlo simulation to study the statistical characteristics of datum scheme variations. A headlamp case study is presented that shows the application procedures and demonstrates that both Taylor series and Monte Carlo methods generate comparable results, but the former offers more efficiency and convenience due to its close form formulation. This approach has found many applications especially in on-site problem solving and fast what-if studies.

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.

Traditional autonomous vehicle perception subsystems that use onboard sensors have the drawbacks of high computational load and data duplication. Infrastructure-based sensors, which can provide high quality information without the computational burden and data duplication, are an alternative to traditional autonomous vehicle perception subsystems. However, these technologies are still in the early stages of development and have not been extensively evaluated for lane detection system performance. Therefore, there is a lack of quantitative data on their performance relative to traditional perception methods, especially during hazardous scenarios, such as lane line occlusion, sensor failure, and environmental obstructions.

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.

For higher mileage vehicles, noise from contaminant ingress is one of the largest durability issues for wheel bearings. The mileage that wheel bearing sealing issues increase can vary due to multiple factors, such as the level of corrosion for the vehicle and the mating components around the wheel bearing. In general, sealing issues increase after 20,000 to 30,000 km. Protecting the seals from splash is a key step in extending bearing life. Benchmarking has shown a variety of different brake corner designs to protect the bearing from splash. This report examines the effect of factors from different designs, such as the radial gap between constant velocity joint (CVJ) slinger and the knuckle, knuckle labyrinth height and varying slinger designs to minimize the amount of splash to the bearing inboard seal. This report reviews some of the bearing seal failure modes caused by splash.

As the fuel economy regulations increase in stringency, many manufacturers are implementing start-stop operation to enhance vehicle fuel economy. During start-stop operation, the engine shuts off when the vehicle is stationary for more than a few seconds. When the brake is released by the driver, the engine restarts. Depending on traffic conditions, start-stop operation can result in fuel savings from a few percent to close to 10%. Gasoline direct injection (GDI) engines are also increasingly available on light-duty vehicles. While GDI engines offer fuel economy advantages over port fuel injected (PFI) engines, they also tend to have higher PM emissions, particularly during start-up transients. Thus, there is interest in evaluating the effect of start-stop operation on PM emissions. In this study, a 2.5L GDI vehicle was operated over the FTP75 drive cycle.

Reliable means for on-board detection of particulate filter failures or malfunctions are needed to meet diagnostics (OBD) requirements. Detecting these failures, which result in tailpipe particulate matter (PM) emissions exceeding the OBD limit, over all operating conditions is challenging. Current approaches employ differential pressure sensors and downstream PM sensors, in combination with particulate filter and engine-out soot models. These conventional monitors typically operate over narrowly-defined time windows and do not provide a direct measure of the filter’s state of health. In contrast, radio frequency (RF) sensors, which transmit a wireless signal through the filter substrate provide a direct means for interrogating the condition of the filter itself.

Development of reliable magnesium (Mg) to steel joining methods is one of the critical issues in broader applications of Mg in automotive body construction. Ultrasonic spot welding (USW) has been demonstrated successfully to join Mg to steel and to achieve strong joints. In this study, corrosion test of ultrasonic spot welds between 1.6 mm thick Mg AZ31B-H24 and 0.8 mm thick galvanized mild steel, without and with adhesive, was conducted. Adhesive used was a one-component, heat-cured epoxy material, and was applied between overlapped sheets before USW. Corrosion test was conducted with an automotive cyclic corrosion test, which includes cyclic exposures of dipping in the 0.5% sodium chloride (NaCl) bath, a constant humidity environment, and a drying period. Lap shear strength of the joints decreased with the cycles of corrosion exposure. Good joint strengths were retained at the end of 30-cycle test.

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.

A new analytical method to aid in the understanding of the organic carbon (OC) phase of particulate matter (PM) from advanced compression ignition (ACI) operating modes, is presented. The presence of NO2 and unburned fuel aromatics in ACI emissions, and the low exhaust temperatures that result from this low temperature combustion strategy, provide the right conditions for the formation of carboxylic acids and nitroaromatic compounds. These polar compounds contribute to OC in the PM and are not typically measured using nonpolar solvent extraction methods such as the soluble organic fraction (SOF) method. The new extraction and detection method employs capillary electrophoresis with electrospray ionization mass spectrometry (CE-ESI MS) and was specifically developed to determine polar organic compounds in the ACI PM emissions. The new method identified both nitrophenols and aromatic carboxylic acids in the ACI PM.

This paper is targeted to engineers who are involved in predicting fatigue life using either the strain-life approach or the stress-life approach. However, more emphasis is given to the strain-life approach, which is commonly used for fatigue life analysis in the ground vehicle industry. It attempts to discuss, modify and extend approaches in fatigue analysis, so they are best suited for structural durability engineers. Fatigue analysis requires the use of material fatigue properties, stress or strain results obtained from finite element analyses or measurements, and load data obtained from multi-body dynamic analysis or road load data acquisition. This paper examines the effects of these variables in predicting fatigue life. Various mean stress corrections, along with their advantages and disadvantages are discussed. Different stress/strain combinations such as signed von Mises, and signed Tresca are examined. Also, advanced methods such as Fatemi-Socie and Bannantine are discussed.

Advances in engine controls and sensor technology are making advanced, direct, high-speed control of engine combustion more feasible. Control of combustion rate and phasing in low-temperature combustion regimes and active control of cyclic variability in dilute SI combustion are being pursued in laboratory environments with high-quality data acquisition systems, using metrics calculated from in-cylinder pressure. In order to implement these advanced combustion controls in production, lower-quality data will need to be tolerated even if indicated pressure sensors become available. This paper examines the effects of several data quality issues, including phase shifting (incorrect TDC location), reduced data resolution, pressure pegging errors, and random noise on calculated combustion metrics that are used for control feedback.

The Energy Flow Method (EFM), which is based on a Finite Element Analysis (FEA) model and its modal frequency response solution is presented in this paper. The energy and power for each subsystem are the primary response and excitation parameters as in the Statistical Energy analysis (SEA) method. This gives a broad-brush prediction by averaging over both frequency and spatial domain. This prediction is useful when uncertainties exist in the model. The FEA model is used to capture the geometry detail, which is critical in mid-frequency vibration. As an example, a five-plate system is studied using various methods, including traditional FEA, SEA and EFM. The last one has been implemented in MSC/NASTRAN. A discussion is given to understand the limitation of SEA and FEA application in mid frequency response.

Drop tower axial crush testing was performed on hat section samples of various steel grades ranging in minimum tensile strength from 410 MPa to 1300 MPa. It was demonstrated that the energy absorption capability increases with the tensile strength of the steel. However, steels of very high strength, greater than 980 MPa tensile strength, exhibited a greater tendency for weld button pullout or material fracture, and thus limited energy the absorption capability. The effect of the closeout plate and the yield strength of the steel on energy absorption were also investigated. FEA simulations were performed and correlated to the experimental results. A flow stress based material criterion is introduced based on the analytical approach to compare the crush performance of steels.

Five different commercially available high-temperature martensitic steels were evaluated for use in a heavy-duty diesel engine piston application and compared to existing piston alloys 4140 and microalloyed steel 38MnSiVS5 (MAS). Finite element analyses (FEA) were performed to predict the temperature and stress distributions for severe engine operating conditions of interest, and thus aid in the selection of the candidate steels. Complementary material testing was conducted to evaluate the properties relevant to the material performance in a piston. The elevated temperature strength, strength evolution during thermal aging, and thermal property data were used as inputs into the FEA piston models. Additionally, the long-term oxidation performance was assessed relative to the predicted maximum operating temperature for each material using coupon samples in a controlled-atmosphere cyclic-oxidation test rig.