Search Results

Since transient vehicle HVAC computational fluids (CFD) simulations take too long to solve in a production environment, the goal of this project is to automatically create a lumped-parameter flow network from a steady-state CFD that solves nearly instantaneously. The data mining algorithm k-means is implemented to automatically discover flow features and form the network (a reduced order model). The lumped-parameter network is implemented in the commercial thermal solver MuSES to then run as a fully transient simulation. Using this network a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track localized temperatures near specific objects (such as equipment in vehicles).

Accurate prediction of in-vehicle powertrain bounce mode is necessary to ensure optimum responses are achieved at driver’s touch points during 4post shake or rough road shake events. But, during the early stages of vehicle development, building a detailed vehicle finite element (FE) model is not possible and often powertrain bounce modes are computed assuming the powertrain to be a stand-alone unit. Studies conducted on FE models of a large SUV with body on frame architecture showed that the stand-alone approach overestimates the powertrain bounce mode. Consequently, there is a need for a simplified version of vehicle model which can be built early on to compute powertrain modes. Previously, representing all the major components as rigid entities, simplified unibody vehicle models have been built to compute powertrain modes. But such an approach would be inaccurate here, for a vehicle with body on frame architecture due to the flexible nature of the frame (even at low frequencies).

Automotive companies are studying to add extra value in their vehicles by enhancing powertrain sound quality. The objective is to create a brand sound that is unique and preferred by their customers since quietness is not always the most desired characteristic, especially for high-performance products. This paper describes the process of developing a brand powertrain sound for a high-performance vehicle using the DFSS methodology. Initially the customer's preferred sound was identified and analyzed. This was achieved by subjective evaluations through voice-of-customer clinics using vehicles of similar specifications. Objective data were acquired during several driving conditions. In order for the design process to be effective, it is very important to understand the relationship between subjective results and physical quantities of sound. Several sound quality metrics were calculated during the data analysis process.

Despite numerous research efforts, there is no reliable and widely accepted tool for the prediction of erosion prone material surfaces due to collapse of cavitation bubbles. In the present paper an Erosion Aggressiveness Index (EAI) is proposed, based on the pressure loads which develop on the material surface and the material yield stress. EAI depends on parameters of the liquid quality and includes the fourth power of the maximum bubble radius and the bubble size number density distribution. Both the newly proposed EAI and the Cavitation Aggressiveness Index (CAI), which has been previously proposed by the authors based on the total derivative of pressure at locations of bubble collapse (DP/Dt>0, Dα/Dt<0), are computed for a cavitating flow orifice, for which experimental and numerical results on material erosion have been published. The predicted surface area prone to cavitation damage, as shown by the CAI and EAI indexes, is correlated with the experiments.

Engine air induction shell noise is a structure borne noise that radiates from the surface of the air induction system. The noise is driven by pulsating engine induction air and is perceived as annoying by vehicle passengers. The problem is aggravated by the vehicle design demands for low weight components packaged in an increasingly tight under hood environment. Shell noise problems are often not discovered until production intent parts are available and tested on the vehicle. Part changes are often necessary which threatens program timing. Shell noise should be analyzed in the air induction system design phase and a good shell noise analytical process and targets must be defined. Several air induction clean side ducts are selected for this study. The ducts shell noise is assessed in terms of material strength and structural stiffness. A measurement process is developed to evaluate shell noise of the air induction components. Noise levels are measured inside of the clean side ducts.

Developing lightweight, stiff and crash-resistant vehicle body structures requires a balance between part geometry and material properties. High strength materials suitable for crash resistance impose geometry limitations on depth of draw, radii and wall angles that reduce geometric efficiency. The introduction of 3rd generation Advanced High Strength Steels (AHSS) can potentially change the relationship between strength and geometry and enable simultaneous improvements in both. This paper will demonstrate applicability of 3rd generation AHSS with higher strength and ductility to replace the 780 MPa Dual Phase steel in a sill reinforcement on the current Jeep Cherokee. The focus will be on formability, beginning with virtual simulation and continuing through a demonstration run on the current production stamping tools and press.

One of the key inputs 1-D transient simulation takes is a detailed front end cooling flow map. These maps that are generated using a full vehicle Three-dimensional Computational Fluid Dynamics (3D CFD) model require expensive computational resources and time. This paper describes how an adaptive sampling of the design space allowed the reduction of computational efforts while keeping desired accuracy of the analysis. The idea of the method was to find a pattern of Design of Experiments (DOE) sampling points for 3D CFD simulations that would allow a creation of an approximation model accurate enough to predict output parameter values in the entire design space of interest. Three procedures were implemented to get the optimal sampling pattern.

It is a challenging task to find an optimal design concept for a truck frame structure given the complexity of loading conditions, vehicle configurations, packaging and other requirements. In addition, there is a great emphasis on light weight frame design to meet stringent emission standards. This paper provides a framework for fast and efficient development of a frame structure through various design phases, keeping durability in perspective while utilizing various weight reduction techniques. In this approach frame weight and stiffness are optimized to meet strength and durability performance requirements. Fast evaluation of different frame configurations during the concept phase (I) was made possible by using DFSS (Design for Six Sigma) based system synthesis techniques. This resulted in a very efficient frame ladder concept selection process.

The automotive door structure experience various static and dynamic loading conditions while going through an opening and closing operation. A typical swing door is attached to the body with two hinges and a check strap. These mechanisms carry the loads while the door is opened. Similarly, while closing the door, the latch/striker mechanism along with the seal around the periphery of the door react all loads. Typically, computer aided engineering (CAE) simulations are performed considering a nominal manufacturing (or build) tolerance condition, that results in one loading scenario. But while assembling the door with the body, the build variations in door mechanisms mentioned above can result in different loading scenarios and it should be accounted for design evaluation. This paper discusses various build tolerances and its effect on door durability performances to achieve a robust door design.

Software systems on electronically controlled diesel truck engines typically provide diagnostic features to enable the engine mechanic to identify and debug system problems. As future systems become more sophisticated, so will the diagnostic requirements. The advantages of serviceability and accuracy found in todays electronic systems must not be allowed to degrade due to this increased sophistication. One method of maintaining a high level of serviceability and accuracy is to place an even greater priority on diagnostics and servicing in the initial design phase of the product than is done today. In particular, three major goals of future diagnostic systems should be separation of component failures from system failures, prognostication of failures and analysis of engine performance. This paper will discuss a system to realize these goals by dividing the diagnostic task into the Electronic System Diagnostics, Engine System Diagnostics and the Diagnostic Interface.

Geometry Tree is a term describing the product assembly structure and the manufacturing process for the product. The concept refers to the assembly structure of the final vehicle (the Part Tree) and the assembly process and tools for the final product (the Process Tree). In the past few years, the Geometry Tree-based quality process was piloted in the FCA US LLC assembly plants and has since evolved into a standardized quality control process. In the Part Tree process, the coordinated measurements and naming convention are enforced throughout the different levels of detailed products to sub-assemblies and measurement processes. The Process Tree, on the other hand, includes both prominently identified assembly tools and the mapping of key product characteristics to key assembly tools. The benefits of directly tying critical customer characteristics to actual machine components that have a high propensity to influence them is both preventive and reactive.

Rear Window Buffeting (RWB) is the low-frequency, high amplitude, sound that occurs in many 4-door vehicles when driven 30-70 mph with one rear window lowered. The goal of this paper is to demonstrate that the mechanisms of RWB are similar to that of sun roof buffeting and to describe the results of several actions suspected in contributing to the severity of RWB. Finally, the results of several experiments are discussed that may lend insight into ways to reduce the severity of this event. A detailed examination of the side airflow patterns of a small Sport Utility Vehicle (SUV) shows these criteria exist on a small SUV, and experiments to modify the SUV airflow pattern to reduce RWB are performed with varying degrees of success. Based on the results of these experiments, design actions are recommended that may result in the reduction of RWB.

The Time Variant Discrete Fourier Transform was implemented as a real-time order tracking method using developed software and commercially available hardware. The time variant discrete Fourier transform (TVDFT) with the application of the orthogonality compensation matrix allows multiple tachometers to be tracked with close and/or crossing orders to be separated in real-time. Signal generators were used to create controlled experimental data sets to simulate tachometers and response channels. Computation timing was evaluated for the data collection procedure and each of the data processing steps to determine how each part of the process affects overall performance. Many difficulties are associated with a real-time data collection and analysis tool and it becomes apparent that an understanding of each component in the system is required to determine where time consuming computation is located.

This paper presents the damping effectiveness of free-layer damping materials through standard Oberst bar testing, solid plate excitation (RTC3) testing, and prediction through numerical schemes. The main objective is to compare damping results from various industry test methods to performance in an automotive body structure. Existing literature on laboratory and vehicle testing of free-layer viscoelastic damping materials has received significant attention in recent history. This has created considerable confusion regarding the appropriateness of different test methods to measure material properties for damping materials/treatments used in vehicles. The ability to use the material properties calculated in these tests in vehicle CAE models has not been extensively examined. Existing literature regarding theory and testing for different industry standard damping measurement techniques is discussed.

The induction hardening process involves a complex interaction of electromagnetic heating, rapid cooling, metallurgical phase transformations, and mechanical behavior. Many factors including induction coil design, power, frequency, scanning velocity, workpiece geometry, material chemistry, and quench severity determine a process outcome. This paper demonstrates an effective application of a numerical analysis tool for understanding of induction hardening. First, an overview of the Caterpillar induction simulation tool is briefly discussed. Then, several important features of the model development are examined. Finally, two examples illustrating the use of the computer simulation tool for solving induction-hardening problems related to cracking and distortion are presented. These examples demonstrate the tool's ability to simulate changes in process parameters and latitude of modeling steel or cast iron.

For many automotive systems it is required to calculate both the durability performance of the part and to rule out the possibility of collision of individual components during severe base shake vibration conditions. Advanced frequency domain methods now exist to enable the durability assessment to be undertaken fully in the frequency domain and utilizing the most advanced and efficient analysis tools (refs 1, 2, 3, 4, 5). In recent years new capabilities have been developed which allow hyper-sized models with multiple correlated loadcases to be processed. The most advanced stress processing (eg, complex von-Mises) and fatigue algorithms (eg, Strain-Life) are now included. Furthermore, the previously required assumptions that the loading be stationary, Gaussian and random have been somewhat relaxed. For example, mixed loading like sine on random can now be applied.

For a light duty truck, the frame is a structural system and it must go through a series of proving ground events to meet fatigue performance requirement. Nowadays, in order to meet stringent CAFE standards, auto manufacturers are seeking to keep the vehicle weight as light as possible. The weight reduction on the frame is a challenging task as it still needs to maintain the strength, safety, and durability fatigue performance. CAE fatigue simulation is widely used in frame design before the physical proving ground tests are performed. A typical frame durability fatigue analysis includes both the base metal fatigue analysis and seam weld fatigue analysis. Usually the gauges of the frame components are dictated by the seam weld fatigue performance so opportunities for weight reduction may exist in areas away from the welds. One method to reduce frame weight is to cut lightening holes in the areas that have little impact on the frame fatigue performance.

During development of new vehicles, CAE driven optimizations are helpful in achieving the optimal designs. In the early phase of vehicle development there is an opportunity to explore shape changes, gage reduction or alternative materials as enablers to reduce weight. However, in later phases of vehicle development the window of opportunity closes on most of the enablers discussed above. The paper discusses a simplified methodology for reducing the weight in design cycle for truck frames using parametric Design of Experiments (DOE). In body-on-frame vehicles, reducing the weight of the frame in the design cycle without down gaging involves introducing lightening holes or cutouts while still maintaining the fatigue life. It is also known that the lightening holes might cause stress risers and be detrimental to the fatigue life of the component. Thus the ability to identify cutout locations while maintaining the durability performance becomes very critical.

A vehicle’s exterior fit and finish, in general, is the first system to attract customers. Automotive exterior engineers were motivated in the past few years to increase their focus on how to optimize the vehicle’s exterior panels split lines quality and how to minimize variation in fit and finish addressing customer and market required quality standards. The design engineering’s focus is to control the deviation from nominal build objective and minimize it. The fitting process follows an optimization model with the exterior panel’s location and orientation factors as independent variables. This research focuses on addressing the source of variation “contributed factors” that will impact the quality of the fit and finish. These critical factors could be resulted from the design process, product process, or an assembly process. An empirical analysis will be used to minimize the fit and finish deviation.

Upper frame deflection of automobile doors is a key design attribute that influences structural integrity and door seal performance as related to NVH. This is a critical customer quality perception attribute and is a key enabler to ensure wind noise performance is acceptable. This paper provides an overview of two simulation methodologies to predict door upper frame deflection. A simplified simulation approach using point loads is presented along with its limitations and is compared to a new method that uses CFD tools to estimate aerodynamic loads on body panels at various vehicle speeds and wind directions. The approach consisted of performing external aerodynamic CFD simulation and using the aerodynamic loads as inputs to a CAE simulation. The details of the methodology are presented along with results and correlation to experimental data from the wind tunnel.