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Studying the kinetic and kinematics of the rim-tire combination is very important in full vehicle simulations, as well as for the tire design process. Tire maneuvers are either quasi-static, such as steady-state rolling, or dynamic, such as traction and braking. The rolling of the tire over obstacles and potholes and, more generally, over uneven roads are other examples of tire dynamic maneuvers. In the latter case, tire dynamic models are used for durability assessment of the vehicle chassis, and should be studied using high fidelity simulation models. In this study, a three-dimensional finite element model (FEM) has been developed using the commercial software package ABAQUS. The purpose of this study is to investigate the tire dynamic behavior in multiple case studies in which the transient characteristics are highly involved.

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).

Idle shake is an important NVH attribute. Vehicles with good NVH characteristics are designed to perform excellent in IDLE and SHAKE conditions. Typically, tactile vibrations at idle are measured at the driver seat and steering wheel. Vibrations caused by engine excitation at idle are passed through several paths to the body structure. The dominant paths being the engine mounts and the half-shafts, either one of them or both can be a major factor influencing the perceived idle vibration in a vehicle. In the past, modeling the half-shafts accurately has been a challenge and often time has been ignored because of modeling complexity. This has led to idle CAE predictions not correlating with test data. The aim of this paper is to describe a finite element modeling method of half-shaft to predict idle vibrations levels.

In Automotive and Aerospace industries, sound package has an important role to control vehicle noise in order to improve passenger comfort and reduce environmental noise pollution. The most known approaches used to model the sound package are the Transfer Matrix Method (TMM) combined with Statistical Energy Analysis (SEA). The Transfer Matrix Method based approach is extensively used and well-validated for predicting the transmission loss and other vibro-acoustic indicators of multi-layer structures. However, to the best of our knowledge, the equivalent damping due to the multilayer has not been addressed yet in the literature, and it's a novel approach. In this paper, simplified formulations using TMM to compute the equivalent damping will be recalled, and an experimental study will be conducted to assess the add-on damping by sound package for different configurations.

Dimensional Engineering concentrates effort in the early design phases to meet the dimensional build objectives in automotive production. Design optimization tools include tolerance stack up, datum optimization, datum coordination, dimensional control plans, and measurement plans. These tools are typically based on the assumption that parts are rigid and tooling dimensions are perfect. These assumptions are not necessarily true in automotive assemblies of compliant sheet metal parts on high volume assembly lines. To address this issue, Finite Element Analysis (FEA) has been increasingly used to predict the behavior of imperfect and deformable parts in non-nominal tooling. This paper demonstrates an application of this approach. The complete analysis is divided into three phases. The first phase is a nominal design gravity analysis to validate the nominal design and tooling.

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.

This paper describes a reliable CAE methodology to model the linear vibratory behavior of windshields. The windshield is an important component in vehicle NVH performance. It plays an integral role in interior cabin noise. The windshield acts as a large panel typically oriented near vertical at the front of vehicle’s acoustic cavity, hence modeling it accurately is essential to have a reliable prediction of cabin interior noise. The challenge to model the windshield accurately rises from the structural composition of different types of windshields. For automotive applications, windshields come in several structural compositions today. In this paper, we will discuss two types of windshield glass used primarily by automotive manufacturers. First type is the typical laminated glass with polyvinyl butyral (PVB) layer and second type is the acoustic glass with PVB and vinyl layers. Acoustic glass improves acoustic characteristics of the glass in a frequency range of ~ 1200 Hz to ~4000 Hz.

This paper describes a study on identifying a suitable thickness for finite element modeling a “deformable washer” to simulate bolted joints for vehicle level durability analysis based on experimental results. First, a test matrix table is introduced, which is based on representative vehicle structures for different bolt/nut sizes, bolt grades, sheet gages, and sheet materials etc. Then coupon tests, both static and fatigue, are illustrated. Next, the corresponding finite element model with different thickness of “deformable washers” and results are presented. Following that, the optimal “deformable washer” thickness is recommended based on statistical parameters (mean and standard deviation) of the relative differences between finite element analysis results and physical test results. Lastly, a case study is demonstrated for the proposed strategy.

In this study, a unique multi-camera three-dimensional digital image correlation (3D-DIC) system was designed and applied to an engine dynamometer cell to measure the displacement and strain of the exhaust manifold while an engine was running in a durability test. In the engine dynamometer cell, the ambient temperature varies from 25°C to 80°C~100°C cyclically and the exhaust manifold experiences high temperatures up to 900°C with high frequency vibrations. In order to obtain reliable data under such conditions, two 3D-DIC systems were designed and set up in the engine dynamometer. One is a high-speed 3D-DIC system, consisting of cameras with a sampling rate of 1250 frames per second. It was used to measure the local displacement of the bolted joint in the exhaust manifold. The high-speed measurement system is able to record the behavior of the bolt during the thermal cycles.

This study outlines a protocol for image data collection acquired from human volunteers. The data set will serve as the foundation of a consolidated effort to develop the next generation full-body Finite Element Analysis (FEA) models for injury prediction and prevention. The geometry of these models will be based off the anatomy of four individuals meeting extensive prescreening requirements and representing the 5th and 50th percentile female, and the 50th and 95th percentile male. Target values for anthropometry are determined by literature sources. Because of the relative strengths of various modalities commonly in use today in the clinical and engineering worlds, a multi-modality approach is outlined. This approach involves the use of Computed Tomography (CT), upright and closed-bore Magnetic Resonance Imaging (MRI), and external anthropometric measurements.

The finite element method (FEM) is used daily in the automotive industry for such purposes as reducing the time of product development and improving the design based on analysis results, followed by later validation by tests in the laboratory and on the proving ground. This paper will present some of the methodology used to develop automotive components by finite element analysis, including procedures to specialize FEM models to obtain quantitative and qualitative results for systems such as body, chassis, and suspension components, as well as validation of the models by experimental data.

Realizing the value of knowledge, corporations are turning to Knowledge Based Engineering (KBE) as a design process. A fuel rail KBE tool was created at Visteon with the purpose of increasing knowledge retention and delivering knowledge based designs to the customer much quicker than with conventional methods. Currently, both engineers and CAD designers are using the Fuel Rail KBE Modeler at Visteon. It has been used on many vehicle programs and has saved the company countless person-hours of development time. The Fuel Rail KBE Modeler is a powerful tool that saves resources through automation of both the design and analysis processes. This paper documents the incorporation of automated FEA capability into the KBE environment.

In current scenario, there is an increasing need to have faster product development and achieve the optimum design quickly. In an automobile air conditioning system, the main function of HVAC third row floor duct is to get the sufficient airflow from the rear heating ventilating and air-conditioning (HVAC) system and to provide the sufficient airflow within the leg locations of passenger. Apart from airflow and temperature, fatigue strength of the duct is one of the important factors that need to be considered while designing and optimizing the duct. The challenging task is to package the duct below the carpet within the constrained space and the duct should withstand the load applied by the passenger leg and the luggage. Finite element analysis (FEA) has been used extensively to validate the stress and deformation of the duct under different loading conditions applied over the duct system.

Vehicle weight reduction is a significant challenge for the modern automotive industry. In recent years, the amount of vehicular components constructed from aluminum alloy has increased due to its light weighting capabilities. Automotive manufacturing processes, predominantly those utilizing various stamping applications, require a thorough understanding of aluminum fracture predictions methods, in order to accurately simulate the process using Finite Element Method (FEM) software or use it in automotive engineering manufacture. This paper presents the strain distribution of A5182 aluminum samples after punch impact under various conditions by Digital Image Correlation (DIC) system, its software also measured the complete strain history, in addition to sample curvature after it was impacted; therefore obtaining the data required to determine the amount of side-wall-curl (Aluminum sheet springback) present after formation.

During the course of automobile Instrument Panel (IP) design development, the occupant head impact CAE simulation on IP are routinely performed to validate FMVSS201 requirements. Based on FMVSS201 requirements, the potential head impact zones on the IP are first identified. Then, the head impact zones are used to locate the various target points that must be impacted on IP. Once the critical target locations on IP are chosen, there are several computational steps that are required to calculate impact angles and head form (HF) center of rotation in reference to target points. Then, CAE engineer performs a repetitive process that involves positioning each individual HF with proper impact angle, assigning initial velocity to HF, and defining surface contacts within the finite element model (FEM). To simplify these lengthy manual steps, a commercially available software HyperMesh® CAE software tool is used to automate these steps. The automation scripting tool is based on TCL programming.

The elevated strength of advanced high strength steels (AHSS) leads to enormous challenges for the sheet metal processing, one of which is hole punching operation. The total tonnage must be estimated at each trimming stage to ensure successful cutting and protect the press machine. This paper presents the effects of hole punch configurations on the punching force with the consideration of punch shape, cutting clearance and material grade. The hole punching experiments were performed with DP590, DP980, DP1180 and one mild steel as a reference. The punching force coefficient is defined and presents a negative correlation with the material strength based on the experimental data. Surface quality was examined to analyze the damage accumulation during the punching process. The cutting mechanisms with various punch shapes were revealed through an extensive finite element simulation study.

Twist spring-back would interfere with stamping or assembling procedures for advanced high strength steel. A “homeopathic” resolution for controlling the twist spring-back is proposed using unbalanced post-stretching configuration. Finite element forming simulation is applied to evaluate and compare the performance for each set of unbalanced post-stretching setup. The post-stretching is effectuated by stake bead application. The beads are separated into multiple independent segments, the height and radii of which can be adjusted individually and asymmetrically. Simulation results indicate that the twist spring-back can be effectively controlled by reducing the post-stretching proximate to the asymmetric part area. Its mechanism is qualitatively revealed by stress analyses, that an additional but acceptable cross-sectional spring-back re-balances the sprung asymmetrical geometry to counter the twist effect.

An experimental method for nondestructive estimation of damage in joints due to high mileage degradation in cars is presented. The method estimates damage by comparing transfer functions of the same car at zero and at high mileage. The potential of the method is demonstrated analytically using a three dimensional concept Finite Element Model (FEM) of a car body to simulate the transfer functions of this car body at zero and at high mileage. The results demonstrate that the method is effective for identifying the damaged joints as well as the relative degree of degradation.

The Los Angeles City Traffic (LACT) brake test is well known acclaimed procedure used by many vehicle manufacturers to assess the brake pad wear behavior and to investigate the Noise, Vibration and Harness (NVH) performance of the brake system. The LACT driving route consists of a set of real-world driving conditions, which has been considered representative of the US passenger vehicle market. The scope of this study is to mimic the LACT test using finite element analysis (FEA) to calculate the wear displacement based on Rhee’s theory. The Leading-edge and trailing edge of the brake pad’s wear tendency is also predicted from the simulation. The finite element model for wear simulation consists of brake system viz., Rotor, Knuckle, Pads, Anchor bracket, Piston, and Caliper.

Reducing emissions and the carbon footprint of our society have become imperatives requiring the automotive industry to adapt and develop technologies to strive for a cleaner sustainable transport system and for sustainable economic prosperity. Electrified hybrid electric vehicles (HEV), plug-in hybrid electric vehicles (PHEV) and range extender powertrains provide potential solutions for reducing emissions, but they present challenges in terms of thermal management. A key requirement for meeting these challenges is accurately to predict the thermal loading and temperatures of an internal combustion engine (ICE) quickly under multiple full-load and part-load conditions. Computational Fluid Dynamics (CFD) and thermal survey database methods are used to derive thermal loading of the engine structure and are well understood but typically only used at full-load conditions.