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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.

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.

In racetrack conditions, brake systems are subjected to extreme energy loads and energy load distributions. This can lead to very high friction surface temperatures, especially on the brake corner that operates, for a given track, with the most available traction and the highest energy loading. Individual brake corners can be stressed to the point of extreme fade and lining wear, and the resultant degradation in brake corner performance can affect the performance of the entire brake system, causing significant changes in pedal feel, brake balance, and brake lining life. It is therefore important in high performance brake system design to ensure favorable operating conditions for the selected brake corner components under the full range of conditions that the intended vehicle application will place them under. To address this task in an early design stage, it is helpful to use brake system modeling tools to analyze system performance.

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.

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.

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.

Global R&D is in its infant stages. Senior executives and their organizations need to develop deeper understanding of the opportunities and challenges of off-shoring R&D. While global pressure will continue to mount to deliver more value at ever lower cost, the labor cost arbitrage break in countries such as China or India will not last forever. The fundamental challenge is to use the current low-cost advantage to build rapidly a sustainable technology, product and service advantage. This requires the development of a balanced local growth strategy that is well adapted to the regional strengths while ensuring a seamless global integration of people, organizations, and processes. This paper focuses on the build-up of GM's R&D activities in India with an emphasis on research in one of the key thrust areas in GM R&D - Automotive Electronics, Controls, and Software. Lessons learned apply also to development.

Steer-by-wire systems (SBW) offer the potential to enhance steering functionality by enabling features such as automatic lane keeping, park assist, variable steer ratio, and advanced vehicle dynamics control. The lack of a steering intermediate shaft significantly enhances vehicle architectural flexibility. These potential benefits led GM to include steer-by-wire technology in its next generation fuel cell demonstration vehicle, called “Sequel.” The Sequel's steer-by-wire system consists of front and rear electromechanical actuators, a torque feedback emulator for the steering wheel, and a distributed electronic control system. Redundancy of sensors, actuators, controllers, and power allows the system to be fault-tolerant. Control is provided by multiple ECU's that are linked by a fault-tolerant communication system called FlexRay. In this paper, we describe the objectives for fault tolerance and performance that were established for the Sequel.

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.

Two thread forming processes, rolling and cutting, were studied for their effects on fatigue in cast aluminum 319-T7. Material was excised from cylinder blocks and tested in rotating-bending fatigue in the form of unnotched and notched specimens. The notched specimens were prepared by either rolling or cutting to replicate threads in production-intent parts. Cut threads exhibited conventional notch behavior for notch sensitive materials. In contrast, plastic deformation induced by rolling created residual compressive stresses in the notch root and significantly improved fatigue strength to the point that most of the rolled specimens broke outside the notch. Fractographic and metallographic investigation showed that cracks at the root of rolled notches were deflected upon initiation. This lengthened their incubation period, which effectively increased fatigue resistance.

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.

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.

The Milford Road Course is a new 2.9 mi (4.6 km), 20 turn, configurable closed course with 135 ft (41 m) of elevation change, constructed at the General Motors Proving Ground in Milford, MI, USA. This facility provides a convenient and safe venue for engineers to evaluate vehicle limit performance over extensive combinations of vertical, lateral and longitudinal acceleration at a wide range of speeds. This paper discusses the vehicle dynamics aspects of the facility design, simulation and construction.

A new process is developed for the aerodynamic shape optimization of racing cars using Computational Fluid Dynamics (CFD). The process is based on using the mesh morphing techniques to create new designs for analysis by morphing the CFD mesh of the original design. The resulting improvements in the analysis turnaround time allow a quick exploration of the design parameters for determining the optimum aerodynamic design. The approach is used to perform a parametric study to optimize a racing car shape for maximum downforce. The analysis procedure used for the CFD analysis is tuned to ensure grid independence and accuracy of the predictions. The parametric study shows that the morpher-based process can quickly and precisely create designs for the CFD analysis. This process can become the foundation for the automated aerodynamic design optimization of the racing cars.

Full-load operation of a small-displacement spark-ignition direct-injection (SIDI) engine was thoroughly investigated by means of computational analysis and engine measurements. The performance is affected by many different factors, which can be grouped as those pertaining to volumetric efficiency, to mixing and stratification, and to system issues, respectively. Volumetric efficiency is affected by flow losses, tuning and charge cooling. Charge cooling due to spray vaporization is often touted as the most significant benefit of direct-injection on full-load performance. However, if wall wetting occurs, this benefit may be completely negated or even reversed. The fuel-air mixing is strongly affected by the injection timing and characteristics at lower engine speeds, while at higher engine speeds the intake flow dominates the transport of fuel particles and resultant vapor distribution. A higher injector flow rate enhances mixing especially at higher engine speeds.