Search Results

When a vehicle with a partially filled fuel tank undergoes sudden acceleration, braking, turning or pitching motion, fuel sloshing is experienced. It is important to establish a CAE methodology to accurately predict slosh phenomenon. Fuel slosh can lead to many failure modes such as noise, erroneous fuel indication, irregular fuel supply at low fuel level and durability issues caused by high impact forces on tank surface and internal parts. This paper summarizes activities carried out by the fuel system team at Ford Motor Company to develop and validate such CAE methodology. In particular two methods are discussed here. The first method is Volume Of Fluid (VOF) based incompressible multiphase Eulerian transient CAE method. The CFD solvers used here are Star CD and Star CCM+. The second method incorporates Fluid-Structure interaction (FSI) using Arbitrary Lagrangian-Eulerian (ALE) formulation.

There is an increasing demand in automated manufacturability analysis of metal castings at the initial stages of their design. This paper presents a system developed for virtual manufacturability analysis of casting components. The system can be used by a casting designer to evaluate manufacturability of a part designed for various manufacture processes including casting, heat treatment, and machining. The system uses computational geometrics and geometric reasoning to extract manufacturing features and geometry characteristics from a part CAD model. It uses an expert system and a design database consisting of metal casting, heat treatment and machining process knowledge and rules to present manufacturability analysis results and advice to the designer. Application of the system is demonstrated for the manufacturability assessment of automotive cast aluminum components.

Recent advancements in simulation software and computational hardware make it realizable to simulate a full vehicle system comprised of multiple sub-models developed in different modeling languages. The so-called, co-simulation allows one to develop a control strategy and evaluate various aspects of a vehicle system, such as fuel efficiency and vehicle drivability, in a cost-effective manner. In order to study the feasibility of the synchronized parallel processing in co-simulation this paper presents two co-simulation frameworks for a complete vehicle system with multiple heterogeneous subsystem models. In the first approach, subsystem models are co-simulated in a serial configuration, and the same sub-models are co-simulated in a parallel configuration in the second approach.

Model-Based Development processes in the automotive industry typically use high-level modeling languages to build the reference models of embedded controllers. One can use formal verification tools to exhaustively verify these design models against their requirements, ensuring high quality models and a reduction in the cost and effort of functional testing. However, there is a gap, in terms of processes and tools, between the informal requirements and the formal specifications required by the verification tools. In this paper, we propose an approach that tries to bridge this gap by (i) identifying the verifiable requirements through a categorization process, (ii) providing a set of templates to easily express the verifiable requirements, and (iii) generating monitors that can be used as specifications in design verification tools. We demonstrate our approach using the Simulink Design Verifier tool for design verification of Simulink/Stateflow models.

In 2006, the Insurance Institute for Highway Safety (IIHS) released a new Low Speed Bumper Test Protocol for passenger cars1. The new test protocol included the development of a deformable barrier that the vehicle would impact at low speeds. IIHS positioned the new barrier to improve correlation to low speed collisions in the field, and also to assess the ability of the bumper system to protect the vehicle from damage. The bumper system must stay engaged to the barrier to protect other vehicle components from damage. The challenge is to identify the bumper system design features that minimize additional cost and mass to keep engagement to the barrier. The results of the Design for Six Sigma analysis identified the design features that increase the stiffness of the bumper system enable it to stay engaged to the barrier and reduce the deflection.

Tappet/bore friction and torque at the camshaft were measured for a direct acting bucket tappet using a cam/tappet friction apparatus. Tappet/bore and cam/tappet friction torque and friction coefficient as a function of cam angle were derived from those measurements. The results showed that, for the particular geometry tested, tappet/bore friction torque accounted for about 13% of the total cam/tappet/bore friction torque at 250 cam rpm. This fraction decreased with increasing speed. Tappet bore friction was greatest at about ± 40 degrees of cam angle, where side loads on the tappet bore were highest. In contrast, earlier results for a center pivot rocker arm design showed tappet bore friction to be negligible.

Rapid Prototyping, Fabrication and Tooling is a process that blends a series of technologies (machines, tools, and methods) capable of generating physical objects directly from a CAD database. The process dramatically reduces the time spent during product development by allowing for fast visualization, verification, iteration, optimization, and fabrication of parts and tools. Many new techniques of tooling have been and are being developed by using rapid fabricated parts. These are having a dramatic impact on both timing and costs throughout the automotive industry. One area that these methods can be utilized to their full potential is motorsports. Of particular interest is the growing use of bridge tooling to provide first article through production intent parts that promote cost effective changes.

There are a number of benefits from Ford Motor Company's participation in motorsports. This paper will describe how an engineering team developed a CAE process to assist in the design of a race car to meet impact requirements, with the technology transfer benefit of improved impact performance of composite structures in passenger cars. In 1997/98, a CAE process was developed and applied in the design and test of Formula One race car composite impact structures. For this particular engineering effort, a Ford proprietary software program, COMP-COLLAPSE, was the primary analysis tool that was utilized to successfully predict impact performance. As a result, COMP-COLLAPSE was used extensively in the design of race car composite impact structures. There were two beneficiaries from this effort: Race Vehicles: Improved vehicle impact performance as well as design improvement in crush efficiency, packaging, weight, and manufacturing.

FMVSS 201U, interior head impact performance is required for each new vehicle program. In the laboratory, testing to this requirement includes laying out the target locations, defining additional robustness target points based on targeting variation, positioning the Free Motion Headform (FMH), impacting each location with the headform and measuring HIC values. The tests may involve some conservative strategies and robustness studies to protect for the worst-case scenarios, where an impact might produce the highest HIC(d) within variations of impact conditions. In order to automate the best practices and procedures for both laboratory and CAE, a process automation environment was used to develop the Interior Head Impact Toolkit (IHIT, pronounced as i-hit). The IHIT software addresses several key testing processes and is grouped into four modules.

This paper presents an enhanced Bayesian based model validation method together with probabilistic principal component analysis (PPCA). The PPCA is employed to address multivariate correlation and to reduce the dimensionality of the multivariate functional responses. The Bayesian hypothesis testing is used to quantitatively assess the quality of a multivariate dynamic system. Unlike the previous approach, the differences between test and CAE results are used for dimension reduction though PPCA and then to assess the model validity. In addition, physics-based thresholds are defined and transformed to the PPCA space for Bayesian hypothesis testing. This new approach resolves some critical drawbacks of the previous method and provides desirable properties of a validation method, e.g., symmetry. A dynamic system with multiple functional responses is used to demonstrate this new approach.

This work presents a statistical approach for simulation based on Monte Carlo method. As an exercise of the method a CAE vehicle dynamics model was specifically created to evaluate the likelihood to meet a given target driving a maneuver for given inputs variations. In the exercise, three different inputs were chosen as stochastic inputs (also called noise factors) and all relevant information about their statistics has been raised, based in components information. The chosen inputs are: front/rear dampers curves, front/rear ride heights and tire surface temperature. A brief description of the Monte Carlo technique is presented. The choice of this method is due to the reduced number of simulations required to have a given accuracy in comparison with other approaches, especially for multivariable system. As output variable for the exercise, the tire patch height was chosen and the resulting probability density function of it is presented.

The behavior knowledge of the vehicle on uphill maneuvers - startability on grade, is an important metric for sizing powertrain components, such as the engine torque, clutch, first and reverse gear ratios, final drive and tire sizes. During the uphill maneuver, all components of the powertrain are subject to efforts that determine the vehicle performance in this condition. The analysis of this maneuver, for a front-wheel-drive vehicle, is evaluated in this article, through a correlation of a computer program developed in Matlab-Simulink, with experimental measurements performed on the vehicle at the track, becoming an important tool for analysis of passenger vehicles subject to these conditions present on Brazilian streets.

As automotive manufacturers continue to increase their use of thermoplastics for interior and exterior components, there is a likelihood of squeaks due to material contacts. To address this issue, Ford's Body Chassis NVH Squeak and Rattle Prevention Engineering Department has developed a tester that can measure friction, and any accompanying audible sound, as a function of sliding velocity, normal load, surface roughness, and environmental factors. The Ford team has been using the tester to address manufacturing plant issues and to develop a database of polymeric material pairings that will be used as a guide for current and future designs to eliminate potential noise concerns. Based upon the database, along with a physical property analysis of the various plastic (viscoelastic) materials used in the interior, we are in the process of developing an analytical model which will be a tool to predict frictional behavior.

Vehicle body with aluminum riveted construction instead of steel welded one will be a big challenge to NVH. In this paper, aluminum and steel rails with the dimensions similar to the rear rail portion of a typical mid-size sedan were fabricated. Rivets were used to assemble the aluminum rails while welds were used to assemble the steel rails. Adhesive, rivet/weld spacing, and rivet/weld location were the three major factors to be studied and their impact on NVH were investigated. The DOE matrix was developed using these three major factors. Modal tests were performed on those rails according to the DOE matrix. The FEA models corresponding to the hardware were built. CAE modal analysis were performed and compared with test data. The current in-house CAE modeling techniques for spot weld and adhesive were evaluated and validated with test data.

Piston slap is a problem that plagues many engines. One of the most difficult aspects of designing to eliminate piston slap is that slight differences in operating conditions and in part geometries from build to build can create large differences in the magnitude of piston slap. In this paper we will describe a design for robustness CAE approach to eliminating piston slap. This approach considers the variations of the significant control factors in the design, e.g. piston pin offset, piston skirt design, etc. as well as the variation in the noise factors the system is subjected to, e.g. assembly clearance, skirt collapse, peak cylinder pressure, cylinder pressure rise rate, and location of peak cylinder pressure. Using analytical knowledge about how these various factors impact the generation of piston slap, a piston design for low levels of piston slap can be determined that is robust to the various noise factors.

Delivering the appropriate material data for CAE analysis of plastic components is not as straight forward as it would seem to be. While a few of the properties typically used by resin manufacturers and material engineers to describe a plastic are useful to the analysis community (density, CLTE), most are not (flexural modulus, notched izod). In addition some properties such as yield stress are defined differently by the analysis community than by the materials community. Lastly, secondary operations such as painting or chrome plating significantly change the behavior of components with plastic substrates. The materials engineering community and the CAE analysis community must work together closely to develop the material data necessary to increase the capability of the analysis. This paper will examine case studies where these issues have required modifications to the material property data to increase the fidelity of the CAE analysis.

Engineering has continuously strived to improve the vehicle development process to achieve high quality designs and quick to launch products. The design process has to have the tools and capabilities to help ensure both quick to the market product and a flawless launch. To achieve high fidelity and robust design, mistakes and other quality issues must be addressed early in the engineering process. One way to detect problems early is to use the math based modeling and simulation techniques of the analysis group. The correlation of the actual vehicle performance to the predictive model is crucial to obtain. Without high correlation, the change management process begins to get complicated and costs start to increase exponentially. It is critical to reduce and eliminate the risk in a design up front before tooling begins to kick off. The push to help achieve a high rate of correlation has been initiated by engineering management, seeing this as an asset to the business.

Hybrid high voltage battery pack is not only heavy mass but also large in dimension. It interacts with the vehicle through the battery tray. Thus the battery tray is a critical element of the battery pack that interfaces between the battery and the vehicle, including the performances of safety/crash, NVH (modal), and durability. The tray is the largest and strongest structure in the battery pack holding the battery sections and other components including the battery disconnect unit (BDU) and other units that are not negligible in mass. This paper describes the mass optimization work done on one of the hybrid batteries using CAE simulation. This was a multidisciplinary optimization project, in which modal performance and fatigue damage were accessed through CAE analysis at both the battery pack level, and at the vehicle level.

This paper presents ‘Virtual Shaker Table’: a CAE method that enables random frequency structural response and random vibration fatigue analyses of a battery system. The Virtual Shaker Table method is a practical and systematic procedure that effectively assesses battery system vibration performance prior to final design, build and testing. A random structural frequency response analysis identifies the critical frequencies and modes at which the battery system is excited by random inputs. Fatigue life may be predicted after PSD stresses have been ascertained. This method enables frequency response analysis techniques to be applied quickly and accurately, thereby allowing assessment of multiple design alternatives. Virtual Shaker Table facilitates an elegant solution to some of the significant challenges inherent to complex battery system design and integration.

The paper will discuss the results of a study to develop lightweight steel proof-of-concept front lower control arm (FLCA) designs that are less expensive and achieve equivalent structural performance relative to a baseline forged aluminum FLCA assembly. A current production forged aluminum OEM sedan FLCA assembly was selected as an aggressive mass target based on competitive benchmarking of vehicles of its size. CAE structural optimization methods were used to determine the initial candidate sheet steel and forged designs. Two (2) sheet steel FLCA designs and one (1) forged steel FLCA design were selected and developed to meet specified performance criteria. An iterative optimization strategy was used to minimize the mass of each design while meeting the specified stiffness, durability, extreme load, and longitudinal buckling strength requirements.