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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.

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.

A common occurrence in computer aided design is the need to make changes to an existing CAD model to compensate for shape changes which occur during a manufacturing process. For instance, finite element analysis of die forming or die tryout results may indicate that a stamped panel springs back after the press line operation so that the final shape is different from nominal shape. Springback may be corrected by redesigning the die face so that the stamped panel springs back to the nominal shape. When done manually, this redesign process is often time consuming and expensive. This article presents a computer program, FESHAPE, that reshapes the CAD or finite element mesh models automatically. The method is based on the technique of volume morphing pioneered by Sederberg and Parry [Sederberg 1986] and refined in [Sarraga 2004]. Volume morphing reshapes regions of surfaces or meshes by reshaping volumes containing those regions.

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.

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.

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.

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.

With the revolutionary advances in computing power and software technology, the future trend of integrating design and CFD analysis software package to realize an automated design optimization has been explored in this study. The integrated process of UG, ICEMCFD, and FLUENT was accomplished using iSIGHT for vehicle Aero/Thermal applications. Process integration, CFD solution strategy, optimization algorithm and the practicality for real world problem of this process have been studied, and will be discussed in this paper. As an example of this application, the results of an underhood thermal design will be presented. The advantage of systematical and rapid design exploration is demonstrated by using this integrated process. It also shows the great potential of computer based design automation in vehicle Aero/Thermal development.

High interest is expressed in using analytical models to eliminate costly driveline tests used to determine the stresses produced in the driveshaft and driveline during resonant operating conditions. This paper discusses an analytical model to simulate the driveline-bending integrity, test procedure. Three major subsystems are modeled in this analytical approach, namely powertrain, rear axle, and driveshaft. Imbalance masses were added on the driveshaft to induce the whirl motion of the driveshaft. The combination of nonlinear Multi-body System Simulation (MSS) and linear Finite Element Analysis (FEA) in the time domain was employed for the evaluation of the dynamic interaction between several parts.

Several methods are currently used to enforce motion in different types of noise and vibration models. Experimentally based FRF models often use a matrix inversion technique to enforce motion. In finite element models, the large mass method is one that is very commonly used. A literature review has shown few guidelines for determining the size of these large masses. In this paper, the relationship between the matrix inversion technique and the large mass method is derived. From this relationship, conditions necessary for these large mass FEM models to converge to the same answers as the matrix inversion technique are derived. These conditions are then used to develop a criterion for determining a smallest possible large mass. Results from a simple model are presented to demonstrate the criterion.

Analytical study of vehicle idle shake performance is standard NVH work within the vehicle development process. Robust design for idle shake performance takes variations into account besides nominal design based performance evaluation. In other words, in addition to the nominal design, Robust Design includes additional evaluations that may incorporate variation due to manufacturing, usage or the environment. This paper presents an example of how to obtain a robust design through performing Robust Optimization on idle shake performance with respect to powertrain mount rates and their tolerance variation. The paper describes a two-phase process that has been systematically implemented to analytically obtain a robust design. In the first phase, performance variation assessment is conducted. Then a Robust Optimization is performed to obtain a robust design.

An automatic optimization process for the aerodynamic design of automotive vehicle shapes is presented. The Computational Fluid Dynamics (CFD) mesh generation and the analysis software packages are coupled for transfer of data and information between the two packages. This communication enables an automated process in which designs are created and analyzed for the aerodynamic drag. New designs are created by morphing the CFD model for the baseline design. The automated process is applied to perform a parametric study on a generic automobile sedan shape. The results show that the process can be used for aerodynamic optimization of any automotive vehicle shape. The turnaround for the automated process is at least an order of magnitude less than the conventional analysis process.

This paper deals with the effects of various approaches for modeling of strain rate effects for mild and high strength steels (HSS) on impact simulations. The material modeling is discussed in the context of the finite element method (FEM) modeling of progressive crush of energy absorbing automotive components. The characteristics of piecewise linear plasticity strain rate dependent material model are analyzed and various submodels for modeling of impact response of steel structures are investigated. The paper reports on the ranges of strains and strain rates that are calculated in typical FEM models for tube crush and their dependence on the material modeling approaches employed. The models are compared to the experimental results from drop tower tests.