Search Results

In this paper, tow hook systems and their functional objectives are briefly introduced. General analysis considerations in strength prediction of a tow hook system are described. These considerations contain nonlinear, clamping and material property simulations. Connections and loading simulation of a tow hook system model are discussed in details. A correlation example of a tow hook system is illustrated. This study shows that detailed modeling of a tow hook system is a fundamental requirement for accurate strength prediction and good correlation between finite element analysis and testing.

In this paper, the methodology of finite element analyses of fastened joints in automotive engineering applications is described in detail. The analyses cover a) the possibility of slippage of the spacer with the design/actual clamp load, and under critical operating loads; b) the strength of the fastener and other structural components comprising the joint under the maximum clamp load. The types of fastened joints, the mechanical characteristics of the joints, the relationship of clamp load to torque, the design and maximum clamp loads, the finite element model meshing and assembly, the non-linearity due to contact, the determination of gaps and stack-up, and the nonlinear material simulation and loading procedures are described. An analysis example of a fastened joint on chassis is also illustrated.

The objective of this paper is to investigate the effect of stamping process on oil canning and dent resistance performances of an automotive roof panel. Finite element analysis of stamping processes was carried out using LS-Dyna to obtain thickness and plastic strain distributions under various forming conditions. The forming results were mapped onto the roof model by an in-house developed mapping code. A displacement control approach using an implicit FEM code ABAQUS/Standard was employed for oil canning and denting analysis. An Auto/Steel Partnership Standardized Test Procedure for Dent Resistance was employed to establish the analysis model and to determine the dent and oil canning loads. The results indicate that stamping has a positive effect on dent resistance and a negative effect on oil canning performance. As forming strains increase, dent resistance increases while the oil canning load decreases.

Accurate motion prediction can be used to evaluate vibrations at seat track and steering wheel. This paper presents the prediction and correlation of truck frame motion from wheel force transducer (WFT) measurements. It is assumed that the method can be used to predict vibrations at seat track and steering wheel for unibody vehicles. Two durability events were used for calculation. WFT measurements were used as inputs applied on frame from suspension. Frame loads were then used as inputs to calculate frame motions using a FEA approach. The predicted frame motions are represented by four exhaust hangers and they are compared with measured motions of the same locations. The correlations include displacement, velocity, and acceleration. It is shown that good correlations are obtained in velocity and displacement. Acceleration shows bigger differences than velocity and displacement.

Cam-phasing is increasingly considered as a feasible Variable Valve Timing (VVT) technology for production engines. Additional independent control variables in a dual-independent VVT engine increase the complexity of the system, and achieving its full benefit depends critically on devising an optimum control strategy. A traditional approach relying on hardware experiments to generate set-point maps for all independent control variables leads to an exponential increase in the number of required tests and prohibitive cost. Instead, this work formulates the task of defining actuator set-points as an optimization problem. In our previous study, an optimization framework was developed and demonstrated with the objective of maximizing torque at full load. This study extends the technique and uses the optimization framework to minimize fuel consumption of a VVT engine at part load.

Current engine development processes typically involve extensive steady-state and simple transient testing in order to characterize the engine's fuel consumption, emissions, and performance based on several controllable inputs such as throttle, spark advance, and EGR. Steady-state and simple transient testing using idealistic load conditions alone, however, is no longer sufficient to meet powertrain development schedule requirements. Mapping and calibration of an engine under transient operation has become critically important. And, independent engine development utilizing accelerated techniques is becoming more attractive. In order to thoroughly calibrate new engines in accelerated fashion and under realistic transient conditions, more advanced testing is necessary.

In this report, the DCX Stress Lab and the Tool Development & Test Support groups investigated automating a resonant bending crankshaft fatigue test. Fatigue testing, in general, is a laborious process since many samples are needed for analysis. This makes development cost and speed dependant on the component test efficiency. In the case of crankshaft resonant bending testing, both cost and speed are influenced by the manual feedback operation needed to run the current procedure. In order to increase the efficiency of this process, this project sought to automate the following tasks: maintaining the load on the part, reacting to resonance changes in the part, mapping resonance changes, logging the number of cycles, and discerning resonance frequency shift failure modes objectively.

Variable Valve Actuation (VVA) technology provides high potential in achieving high performance, low fuel consumption and pollutant reduction. However, more degrees of freedom impose a big challenge for engine characterization and calibration. In this study, a simulation based approach and optimization framework is proposed to optimize the setpoints of multiple independent control variables. Since solving an optimization problem typically requires hundreds of function evaluations, a direct use of the high-fidelity simulation tool leads to the unbearably long computational time. Hence, the Artificial Neural Networks (ANN) are trained with high-fidelity simulation results and used as surrogate models, representing engine's response to different control variable combinations with greatly reduced computational time. To demonstrate the proposed methodology, the cam-phasing strategy at Wide Open Throttle (WOT) is optimized for a dual-independent Variable Valve Timing (VVT) engine.

Vehicle thermal protection is an important aspect of the overall vehicle development process. It involves optimizing the exhaust system routing and designing heat shields to protect various components that are in near proximity to the exhaust system. Reduced time to market necessitates an efficient process for thermal protection development. A robust procedure that utilizes state of the art CFD simulation techniques proactively during the design phase is described. Simulation allows for early detection of thermal issues and development of countermeasures several months before prototype vehicles are built. Physical testing is only used to verify the thermal protection package rather than to develop heat shields. The new procedure reduces the number of physical tests and results in a robust, efficient methodology.

This report explores the relationship of different failure criteria - specifically, surface cracks, stiffness changes, and two-piece failures - on rolled, ductile, cast-iron crankshafts. Crankshaft samples were closely monitored throughout resonant bending fatigue testing and were taken to near complete fracture. By monitoring resonance shifts of the samples during testing, stiffness changes and cracks were monitored. These data showed that an accelerating frequency shift was sufficient to indicate imminent two-piece failure and that this condition can be used as a failure criterion. Fatigue studies on two different crankshafts using this failure criterion were compared to those using a surface crack failure criterion. This comparison showed that using the surface crack failure criterion erroneously decreased the apparent fatigue life of the crankshaft significantly.

Computer applications have been widely used to assist product design. The successes and sophistication of computer aided engineering (CAE) techniques are respectfully recognized in this field. CAE applications in the manufacturing area however are still developing, although the manufacturing community is increasingly starting to pay attentions to computer simulations in its daily workings. This paper will briefly introduce some of these applications and promote awareness of computer simulations in manufacturing area. It contains four main sections: finite element analysis (FEA) in machining fixture design, FEA applications in component assembly, machining process simulations and machining vibrations in the milling operation. Each section comes with a practical case study, potential benefits are identified and conclusions are presented by using an integrated design and analysis approach.

The emerging Variable Valve Timing (VVT) technology complicates the estimation of air flow rate because both intake and exhaust valve timings significantly affect engine's gas exchange and air flow rate. In this paper, we propose to use Artificial Neural Networks (ANN) to model the air flow rate through a 2.4 liter VVT engine with independent intake and exhaust camshaft phasers. The procedure for selecting the network architecture and size is combined with the appropriate training methodology to maximize accuracy and prevent overfitting. After completing the ANN training based on a large set of dynamometer test data, the multi-layer feedforward network demonstrates the ability to represent air flow rate accurately over a wide range of operating conditions. The ANN model is implemented in a vehicle with the same 2.4 L engine using a Rapid Prototype Controller.

A predictive automatic gear shift system is currently under development. The system optimizes the gear shift process, taking the conditions of the road ahead into account, such that the fuel consumption is minimized. An essential part of the system is a module that predicts the vehicle speed dynamics: This calculates a speed trajectory, i.e. the most probable vehicle speed the driver will desire for the upcoming section of the route. In the paper the theoretical background for predicting the vehicle speed, and simulation results of the predictive shift algorithm are presented.

For a vehicle or repairable system, incidents (conditions) are neither necessarily independent nor identically distributed. Therefore, traditional statistical distributions like Weibull, Normal, etc, are no longer valid to estimate reliability. The Non-homogeneous Poisson process (NHPP) model can be used to predict reliability and warranty of the field product. It can also measure the reliability improvement during the development cycle. The NHPP model is discussed in this paper. In applying a NHHP model to reliability data on a repairable system, one may have few or no failures. This paper presents the I/100 and reliability derivations when the parameter β in the ROCOF function is assumed to have a known value.

Loads generated during assembly may cause significant stress levels in components. Under test conditions, these stresses alter the mean stress which in turn, alters the fatigue life and critical stress area of the components as well. This paper describes the Finite Element Analysis (FEA) procedure to evaluate behavior of a cast aluminum wheel subjected to the rotary fatigue test condition as specified in the SAE test procedure (SAE J328 JUN94). Fatigue life of the wheel is determined using the S-N approach for a constant reversed loading condition. In addition, fatigue life predictions with and without clamp loads are compared. It is concluded that the inclusion of clamp load is necessary for better prediction of the critical stress areas and fatigue life of the wheel.

In automotive industry, all passenger vehicles are treated with damping materials to reduce structure borne noise. The effectiveness of damping treatments depends upon design parameters such as choice of damping materials, locations and size of the treatment. This paper proposes a CAE (Computer Aided Engineering) methodology based on finite element analysis to optimize damping treatments. The developed method uses modal strain-energy information of bare structural panels to identify flexible regions, which in turn facilitates optimization of damping treatments with respect to location and size. The efficacy of the method is demonstrated by optimizing damping treatment for a full-size pick-up truck. Moreover, simulated road noise performances of the truck with and without damping treatments are compared, which show the benefits of applying damping treatment.

Recently, many authors have attempted to represent an automobile body in terms of experimentally derived frequency response functions (FRFs), and to couple the FRFs with a FEA model of chassis for performing a total system dynamic analysis. This method is called Hybrid FEA-Experimental FRF method, or briefly HYFEX. However, in cases where the chassis model does not include the bushing models, one can not directly connect the FRFs of the auto body to the chassis model for performing a total system dynamic analysis. In other cases when the chassis model includes the bushings, the bushing dynamic rates are modeled as constant stiffness rather than frequency dependent stiffness, the direct use of the HYFEX method will yield unsatisfactory results. This paper describes how the FRF's of the auto body and the frequency dependent stiffness data of the bushings can be combined with an appropriate mathematical formulation to better represent the dynamic characteristics of a full vehicle.

Springback study on a Dodge Ram fender outer panel is detailed in this paper. A simple measurement fixture is designed for the panel, wherein non-contact laser scan technology is applied The measurement data are compared with the original CAD design surface and deviation contour maps are obtained. Consistency of measurement is studied at different sections among three samples. Details of FEA simulations are outlined. The comparison between measurement and simulation prediction is summarized. A method to describe the consistency of measurement and the accuracy of simulation prediction is proposed. The targets for measurement consistency and simulation accuracy are verified. A sensitivity analysis is also performed to investigate various simulation input parameters.

Laminated steel sheets sandwiched with a polymer core are increasingly used for automotive applications due to their vibration and sound damping properties. However, it has become a major challenge in finite element modeling of laminated steel structures and forming processes due to the extremely large differences in mechanical properties and in the gauges of the polymer core and the steel skins. In this study, circular cup deep drawing and V-bending experiments using laminated steels were conducted in order to develop a modeling technique for laminate forming processes. The effectiveness of several finite element modeling techniques was investigated using the commercial FEM code LS-Dyna. Furthermore, two production parts were selected to verify the modeling techniques in real world applications.

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.