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A greater understanding of where fuel energy is being demanded from a vehicle system standpoint is necessary for developing more fuel efficient vehicles. This paper presents an overview of the development and application of a vehicle energy analysis methodology and a MATLAB®/Simulink® based tool that uses empirical data and first principles to identify vehicle subsystem energy supply and demand. An accurate analysis requires the tool to be populated with chassis dynamometer drive cycle data as well as vehicle and component information. The tool can be used to investigate vehicle system energy requirements, prevailing fuel economy factors, and incremental hypothetical fuel saving scenarios that could not otherwise be measured due to inherent test-to-test variability.

The staircase fatigue testing method is a recognized method for determining the fatigue limit of powertrain components. The purpose of this paper is to improve upon existing standards by adding common practices that will ensure a higher degree of statistical accuracy in the data. This includes specifying appropriate sample sizes, stress increments and initial load conditions, as well as making suggestions for appropriate methods of analyzing the data. Two methods (Dixon and Mood method and probit analysis method) are selected and compared in terms of relative percent difference on four parameters (mean, standard deviation, B10 fatigue strength and B50 fatigue strength). The staircase data are obtained by simulations from normal and lognormal fatigue limit distributions.

This paper describes a program of coastdown and wind tunnel tests conducted with the objective of establishing a correlation between the aerodynamic drag force measured at the Lockheed-Martin Low-Speed Wind Tunnel (LSWT) and that inferred from coastdown results on the test track. The result of this correlation establishes, in principle, the capability to project what the aerodynamic drag force inferred by a future coastdown test will be (for a future, as-yet unavailable property) based on a current database of wind tunnel results. The correlation is accompanied by a rigorous uncertainty analysis to assess the quality of the correlation and its supporting data.

Historically, pump noise can be a contributor to customer dissatisfaction with automatic transmissions. In this paper, a Shainin experiment was conducted to identify all probable root causes for pump noise on a production RWD transmission. Sample transmissions were selected following subjective evaluations. Noise was objectively measured in the lab using a microphone and an accelerometer. The study was conducted following a systematic Shainin statistical engineering methodology, which included the following major steps: selection of the test measure using the isoplot technique, selection of Best of Best (BOB) and Worst of Worst (WOW) transmissions, assessment of assembly variation, component search, and pair-wise comparisons. The study successfully highlighted the key variables on the drive gear involute profile, which are now being tightly controlled for improved noise characteristics.

In the past several years there has been a significant effort to increase the reliance on CAE technology to guide the vehicle design process, with the accompanying effort to reduce or eliminate vehicle prototype testing during the early design phase. Since little or no representative hardware is available early in the design, a tool is needed which allows NVH Development Engineers to subjectively experience the results of NVH CAE model predictions in a realistic driving environment. This paper documents the development of a high fidelity NVH simulator, including both audio and vibration, and the integration of this simulator into an “operator-in-the-loop” Driving Simulator. The key development of this system is its ability to incorporate NVH CAE predictions into the simulated driving environment.

In this paper, loads acting on driveline components during an entire proving ground (PG) durability schedule are used to demonstrate the methodology of optimizing driveline performance reliability using both physical and computational methods. It is well known that there is an effect of driver variability on the driveline component loads. Yet, this effect has not been quantified in the past for lack of experimental data from multiple drivers and reliable data analysis methods. This paper presents the data reduction techniques that are used to identify the extreme driver performance and to extrapolate the short-term measurement to long-term data for driveline performance reliability. The driveline loading variability is made evident in the rotating moment histogram domain. This paper also introduces the concept for a simulation model to predict the driveline component loads based on a complete proving grounds schedule. A model-to-test correlation is also performed in this paper.

During the initial vehicle design phase and as the first prototypes are built, extensive on-board instrumentation and data acquisition is required at the proving grounds (PG). The data is used for various types of testing and analysis. During this phase of development very few parts and assembly components are available for physical test. The objective is to develop a component test for the truck box. This test can be run without suspension parts during the early stages of the vehicle development. A further objective is to correlate the test to FEA models and actual Proving Ground full vehicle test results.

The performance of a large-volume production torque converter is slightly different from those of development prototype due to the core leakage flow. The sealing gap between the stator crown and pump or turbine core of the production converter is usually larger than that of prototypes because of fabrication method and tolerances. In this work, the core leakage flow of torque converter was investigated using CFD. The core region was modeled and coupled together with other three major components of a converter. Studies show that for a particular converter the core leakage flow could result in a 3.6% stall torque ratio reduction and a 2% peak efficiency decrease. The effects of sealing gap dimensions were also studied. Computational investigations in this work indicated that the variation of input K factor with input torque level observed in dyno tests is due to the cavitation in the torque converter.

To improve vehicle launch feeling, the powertrain torque output needs to be largely increased. Compared with modifications to engine, transmission, and axle, one of the most inexpensive ways of achieving this goal is to modify the torque converter to get a higher stall torque ratio. In other applications, in order to lower engine speed for better fuel economy, and to match with a higher output engine, a converter with higher torque capacity (lower K factor) is also often desired. In some case of small-volume production, the torque converter modifications are limited to the stator only in order to reduce the manufacturing cost. In the present study, the engineering CFD simulations were used to develop new stators for stall torque ratio and K factor improvement. The flow fields of both baseline and modified torque converters were simulated. The overall performances of the converter were calculated from the flow field data, and correlated with the dyno test data.

Based on the results of “An Evaluation of the Mechanical Properties of Wheel Force Sensors and their Impact on to the Data Collected During Different Driving Manoeuvres” Herrmann et al. (SAE Paper 05M-254) a second, detailed investigation has been started to acquire additional information. In this previous investigation, it has been found out, that a difference in mass can be clearly identified in the signals. The current paper summarizes the results of a detailed investigation, which has been performed at DaimlerChrysler Stress Lab in Auburn Hills, with a fully equipped vehicle - a set of 2/4 Wheel Force Sensors plus several acceleration sensors as well. Through careful research and testing it is expected that the differences in the dynamic behavior can be specified with better accuracy than in the previous study.

At the initial accessory drive system design stage, a model was created using commercial CAE software to predict the dynamic response of the pulleys, tensioner motion and pulley slip. In a typical 6 cylinder automotive accessory drive systems, the first system torsional mode is near the engine idle speed. The combination of these two events could generate numerous undesirable noise and vibration effects in the system. Data acquisition on a firing engine with a powertrain dynamometer confirmed the computer model's results. Correlations are then developed and established based on results between the firing engine to the CAE model to increase confidence in the generated model. Further system optimization through design modifications are used to tune the system to minimize the overall system dynamics.

Durability of automotive structures is a primary engineering consideration that is required to be assessed at every design and development stage. Due to limitations of the analytical and experimental tools, the current practice in the automotive industry is to conduct a new data acquisition over a proving ground schedule whenever there are changes in the suspension parameters. This is a time-consuming and expensive operation. This paper provides guidelines for product teams to determine if a new vehicle data acquisition is needed when there are changes in vehicle parameters, and the corresponding effect on Road Test Simulator (RTS) drive file development. The application of this methodology to a truck with and without tuned suspension parameters is described in detail.

The Controller Area Network (CAN) provides the user with several parameters to configure the bit timing, sampling point, and bit rate. With this flexibility comes some complexity in choosing the correct values for these parameters and properly configuring the bit rate. A given bit rate can be achieved by setting these parameter in more than one way. It is also possible to incorrectly configure these parameters and achieve a close enough bit rate that will allow the system to function but not perform in an optimized manner. This paper discusses how to calculate the bit rate and how to choose some of these parameters. A set of equations were developed and used in an example to configure the bit rate for a PIC18FXX8 CAN controller.

A Draw Bead Simulator (DBS), with modified draw beads, was employed in this study to understand the springback behavior of sheet metal subjected to multiple bending-unbending cycles. The investigations were carried out in both the rolling and the transverse rolling directions on four types of materials: Electro-Galvanized DQ steel, light and heavy gauge Hot-Dip Galvanealed High Strength Steels, and Aluminum alloy AL6111. The sheet geometries, thickness strains, pulling forces and clamping forces were measured and analyzed for the purpose of establishing a benchmark database for numerical predictions of springback. The results indicate that the springback curvature changes dramatically with the die holding force. The conditions at which the springback is minimized was observed and found to depend on the material properties and the sheet thickness. Analysis with an implicit FEM showed that the predicted and the experimental results are in very good agreement.

The springback behavior might be different due to different gap clearances between die and punch. A study using FEA simulation is done to investigate the die gap effect. A 3D brick element and an explicit-implicit method are employed to investigate a few simple problems. A draw form, a crash form with an upper pad and a flange form are investigated separately. Numisheet’93 2D draw bending springback problem is also investigated using an explicit dynamic code. Comparisons between springback simulation results on several different die gaps are illustrated. The Kirchhoff assumption of C° shell element and the Mindlin/Love assumption of thin shell element are also examined on different cases. A case study then is performed on a rail type panel. Conclusions and recommendations for future studies are summarized.

Throughout its history, the automobile has served the utilitarian purpose of transportation quite well. However, until recently, vehicle occupants have had little else to do while proceeding from point "A'' to point "B.'' The phenomenal improvements in computing and communication technologies promise to evolve the driving experience. Like never before, new opportunities to make driving more efficient and engaging are becoming available. The challenge will be to develop the right combination of technology, safety, design and user interface that creates a product popular with customers.

This paper will provide an overview of the need, requirements, and constraints governing the development and application of polymer composites in automotive body components. It will discuss the efforts underway to lead and support the technology developments required for the cost-effective application of these new materials in mass-produced vehicles. The requirements and constraints of customer-driven, mass-produced, energy-efficient vehicles with uncompromised cost, capacity and performance, drive careful consideration of an injection-molded thermoplastic approach to a composite automotive body. Recent progress with this approach will be reported and some next steps examined.

An extensive digital simulation study on lift devices that interact with human operators in DaimlerChrysler automotive assembly plants has been initiated and deployed. This digital mock-up of human-machine workcells is to scientifically evaluate and further certify a number of typical commercial lift devices that are served in car-assembly operations. The entire model is based on human biomechanical Jacobian relationship, as a fundamental kinematic structure, to predict human body instantaneous joint-torque distribution when the human is working with a certain payload. The developed modeling and simulation system will play a pivotal role in proactive ergonomic prediction, verification and digital certification in car advance manufacturing engineering processes.

A springback study on three rail type panels is summarized. Numisheet'96 S-rail, A/S P rail II and a Daimlerchrysler rail are presented with experiment data and FEA simulation predictions. The details of the measurement on experiment samples and simulation models are illustrated. The comparison between the experiment data and the simulation results from four different softwares is made on separate cases. The correlation between experiment data and simulation results is analyzed.

Transfer Path Analysis (TPA) is a widely used methodology in Noise, Vibration and Harshness (NVH) analysis of motor vehicles. Either it is used to design a vehicle from scratch or it is applied to root cause an existing NVH problem, TPA can be a useful tool. TPA analysis is closely related to the concept of partial contribution. The very basic assumption in TPA is that the summation of all partial contributions from different paths constitutes the total response (which could be either tactile or acoustic). Another popular concept in NVH analysis of vehicles is the component sensitivity. Component sensitivity is a measure of how much the response changes due to a change in one of the components of the system, i.e., the thickness of a panel or elastic rate of an engine mount. Sensitivity rates are more popular among CAE/Simulation community, simply because they are reasonably easy to calculate using mathematical models.