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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.

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.

Static and dynamic strength tests were performed on spot welded specimens made of dual-phase (DP) 780 and mild steels (DQSK). Lap-shear (LS) and cross-tension (CT) as well as a new mixed mode specimen were studied using MTS hydraulic universal testing machine for static tests and drop weight tower for dynamic tests. Three weld nugget sizes were made for each steel and CT and LS. DP780 with one weld size was also tested in mixed mode. Load and displacement as functions of time and fracture mode of the spot welds were recorded. Representative data are reported in this paper.

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.

A DFSS study identified a new mechanism for clamp load loss in aluminum threads due to thermal cycling. In bolted joints tightened to yield, the difference in thermal expansion between the aluminum and steel threads can result in a loss of clamp load with each thermal cycle. This clamp load loss is significantly greater than the loss that can be explained by creep alone. A math model was created and used to conduct a robust analysis. This analysis led to an understanding of the design factors necessary to reduce the cyclic clamp load loss in the aluminum threads. This understanding was then used to create optimized design solutions that satisfy constraints common to powertrain applications. Estimations of clamp load loss due to thermal cycling from the math model will be presented. The estimates of the model will be compared to observed physical test data. A robust analysis, including S/N and mean effect summary will be presented.

Springback is a major concern in stamping of advanced high strength steels (AHSS). The existing computer simulation technology has difficulty predicting this phenomenon accurately even though it is well developed for formability simulations. Great efforts made in recent years to improve springback predictions have achieved noticeable progress in the computational capability and accuracy. In this work, springback simulation studies are conducted using FEA software LS-DYNA®. Various parametric sensitivity studies are carried out and key variables affecting the springback prediction accuracy are identified. Recently developed simulation technologies in LS-DYNA® are implemented including dynamic effect minimization, smooth tool contact and newly developed nonlinear isotropic/kinematic hardening material models. Case studies on lab-scale and full-scale industrial parts are provided and the predicted springback results are compared to the experimental data.

This paper presents the development of a transmission closed loop pressure control system. The objective of this system is to improve transmission pressure control accuracy by employing closed-loop technology. The control system design includes both feed forward and feedback control. The feed forward control algorithm continuously learns solenoid P-I characteristics. The closed loop feedback control has a conventional PID control with multi-level gain selections for each control channel, as well as different operating points. To further improve the system performance, Robust Optimization is carried out to determine the optimal set of control parameters and controller hardware design factors. The optimized design is verified via an L18 experiment on spin dynamometer. The design is also tested on vehicle.

Development and integration of the cooling system for an automotive vehicle requires a balancing act between several performance and styling objectives. The cooling system needs to provide sufficient air for heat rejection with minimal impact on the aerodynamic drag, styling requirements and other criteria. An optimization of various design parameters is needed to develop a design to meet these objectives in a short amount of time. Increase in the accuracy of the numerical predictions and reduction in the turn-around time has made it possible for Computational Fluid Dynamics (CFD) to be used early in the design phase of the vehicle development. This study shows application of the CFD for robust design of the engine cooling system.

The component being formed experiences some type of prestrain that may have an effect on its fatigue strength. This study investigated the forming effects on material fatigue strength of dual phase sheet steel (DP600) subjected to various uniaxial prestrains. In the as-received condition, DP600 specimens were tested for tensile properties to determine the prestraining level based on the uniform elongation corresponding to the maximum strength of DP600 on the stress-strain curve. Three different levels of prestrain at 90%, 70% and 50% of the uniform elongation were applied to uniaxial prestrain specimens for tensile tests and fatigue tests. Fatigue tests were conducted with strain controlled to obtain fatigue properties and compare them with the as-received DP600. The fatigue test results were presented with strain amplitude and Neuber's factor.

Tensile measurements and fracture surface analysis of low carbon heat-treated boron steel are reported. Tensile coupons were quasi-statically deformed to fracture in a miniature tensile testing stage with custom data acquisition software. Strain contours were computed via a digital image correlation method that allowed placement of a digital strain gage in the necking region. True stress-true strain data corresponding to the standard tensile testing method are presented for comparison with previous measurements. Fracture surfaces were examined using scanning electron microscopy and the deformation mechanisms were identified.

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.

Simultaneously obtaining a linear temperature control curve along with the correct temperature stratification at module outlets is one of the most difficult tasks in developing an automotive HVAC module. Traditionally, Computational Fluid Dynamics (CFD) development of temperature control linearity has been accomplished by iteratively adjusting the location, size and orientation of baffles which redirect warm and cold airstreams. This approach demands considerable interaction from the engineer in building the computational mesh, defining boundary and operating conditions and post processing the simulation results. The present study was conducted to investigate the optimization of HVAC temperature regulation curves using the multi-objective optimization code modeFrontier (1, 3) in conjunction with CFD code, Fluent (2). An auxiliary HVAC module was selected for the present study.

Laminated steel has been increasingly applied in automotive products for vibration and noise reduction. One of the major challenges the laminated steel poses is how to simulate forming processes and predict formability severity with acceptable correlation in production environment, which is caused by the fact that a thin polymer core possesses mechanical properties with significant difference in comparison with that of steel skins. In this study a cantilever beam test is conducted for investigating flexural behavior of the laminated steel and a finite element modeling technique is proposed for forming simulation of the laminated steel. Two production panels are analyzed for formability prediction and the results are compared with those from the try-out for validation. This procedure demonstrates that the prediction and try-out are in good agreement for both panels.

Managing (minimizing and optimizing) the total mass of a vehicle is recognized as a critical task during the development of a new vehicle, as well as throughout its production lifecycle. This paper summarizes a literature review of, and investigation into, the strategies, methods and best practices for achieving low total mass in new vehicle programs, and/or mass reductions in existing production vehicle programs. Empirical and quantitative data and examples from the automotive manufacturers and suppliers are also provided in support of the material presented.

The optimal selection of vehicle body and powertrain mounts from “mount libraries” is one of the major undertakings to achieve optimal vehicle dynamics and N&V performance through the reuse of existing mount designs. The great challenges of the process are due to the facts that conventional optimization procedures, either through simulation or DOE, can not be used directly because the stiffness rates of the mounts are scattered and bundled. Sorting out the best through hardware tests is generally unrealistic simply due to the huge number of mount combinations. This paper presents a new approach to the optimal mount selection, and demonstrates through applications that it is efficient and reliable. This approach characterizes a mount by its effective stiffness rate and evaluates its deviation from an associated target. Continuous dummy variables are used to determine the selection targets through conventional processes for performance optimization.

Durability requirements for exhaust materials have resulted in the increased use of stainless steels throughout the exhaust system. The conversion of carbon steel exhaust flanges to stainless steel has occurred on many vehicles. Ferritic stainless steels are commonly used for exhaust flanges. Flange construction methods include stamped sheet steel, thick plate flanges and powder metal designs. Flange material selection criteria may include strength, oxidation resistance, weldability and cold temperature impact resistance. Flange geometry considerations include desired stiffness criteria, flange rotation, gasket/sealing technique and vehicle packaging. Both the material selection and flange geometry are considered in terms of meeting the desired durability and cost. The cyclic oxidation performance of the material is a key consideration when selecting flange materials.

The main objective of this paper was to determine if the vehicle performance can be maintained with a reduced mass cradle structure. Aluminum and magnesium cradles were compared with the baseline steel cradle. First, the steel chassis alone is analyzed with the refined finite element model and validated with experimental test data for the frequencies, normal modes, stiffnesses and the drive-point mobilities at various attachment mount/bushing locations. The superelement method in conjunction with the component mode synthesis (CMS) technique was used for each component of the vehicle such as Body-In-White, Instrument Panel, Steering Column Housing & Wheel, Seats, Cradles, CRFM, etc. After assemblage of all the superelements, analysis was carried out by changing the front and rear cradle gauges and the material properties. The drive-point mobility response was computed at various locations and the noise (sound pressure) level was calculated at the driver and passenger ears.

This paper presents a pioneer work and first time application of Multi Objective Robust Optimization to analytically improve Idle Shake Performance. The method is developed to obtain a robust design with multiple objectives under consideration along with managing material property variation. It was a Robust Optimization on top of Multi Objective Genetic Algorithm, Robu-MOGA. The design variables in the study included the nominal values and tolerances of Sound Transmission Loss property, and interior material Absorption property. The analytical objective was not only to minimize the peak airborne noise at each specified frequency, but also to reduce the total cost and the total mass of the materials. In the study, AutoSEA (statistical energy analysis) from ESI Software, Inc. was used as the solver. AutoSEA was integrated with iSIGHT from Engineous Software, Inc.

Brake insulators often offer optimal solutions to squeal noise. In the process of engineering solutions to reduce the brake noise, a system-level finite element complex eigenvalue analysis is often used and has gained popularity in recent years. Models of insulators have also been proposed for system-level evaluation, however many challenges remain in efficiently implementing an insulator model, owing to complexities of the insulator component model. The complexities arise from the visco-elastic behavior (primarily the frequency and temperature dependence), and the thin polymer/steel multi-layer nature of the construction - typical in an insulator. As a first part of a joint investigation, this paper explores the nature of frequency and temperature dependence in insulator models and reduces the cumbersome multi-layer model into a simpler form that can be more easily implemented in a typical brake system stability analysis.