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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.

In this paper, responses from a vehicle's suspension, chassis and body, are used to demonstrate a methodology to optimize physical test results. It is well known that there is a variability effect due to an increase of wheel unsprung mass (due to loads measurement fixturing), tire pressure, speed, etc. This paper quantifies loading variability due to Wheel Force Transducer (WFT) unsprung mass by using a rainflow cycle counting domain. Also, presents a proving ground-to-test correlation study and the data reduction techniques that are used in road simulation test development to identify the most nominal road load measurement. Fundamental technical information and analytical methodology useful in overall vehicle durability testing are discussed. Durability testing in a laboratory is designed to correlate fatigue damage rig to road. A Proving Ground (PG) loading history is often acquired by running an instrumented vehicle over one or more PG events with various drivers.

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.

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.

The design of occupant restraint systems in the automotive industry has shifted from an empirical approach to a computer aided analysis approach for many years now. Various finite element software programs have been applied in crash safety analysis, and multi-body dynamics codes have been successfully used where quick system response times were required. Most new vehicle programs are analyzed by the use of finite element tools that were used for previous program projects. Software that has specific occupant protection features may be coupled with these finite element tools, or new vehicle programs may be developed from scratch by using one tool that does all, i.e. a tool where the multi-body dynamics are integrated into the finite element method. Both these approaches will be elaborated as valid tools for occupant protection analysis. At first, the coupling between the finite element crash program LS-DYNA and the F.E.

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.

Hot Isostatic Pressing (HIP) has been routinely used to densify castings for aerospace and medical applications for over 30 years. While HIP is widely known to improve the toughness and fatigue life of castings through the healing of internal porosity, it has been perceived as too expensive for most cast aluminum alloys for automotive applications. Recent developments suggest that the cost effectiveness of certain special HIP processes should be revisited due to reductions in process cost and improvements in throughput. This paper will evaluate the Densal® II process applied to a front aluminum steering knuckle. Two casting processes representing differing levels of relative cost and quality were evaluated. The first was Alcoa's VRC/PRC process, a metal mold process with bottom fill, evacuation before fill and pressurization after fill. This is considered to be a premium quality, but higher cost casting process that is already qualified for this application.

Traditionally, high-strength low-alloy (HSLA) steel is used for automotive vehicle weight reduction in the North American automotive industry. Dual phase (DP) high strength steel has gained great attention because it provides a combination of high strength and good formability. The main advantage of DP steel is the high ratio of tensile strength to yield strength, which provides more flexibility in stamping and higher energy absorption in a component crush event. This study compares the performances of DP and HSLA steel grades in stamping processes and component crush events, as shown in a typical automotive unibody inner rail. Simulation results show that DP steel offers more uniform strain distribution, improved formability, and better crush performance than conventional HSLA steel.

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.

Silicon Carbide (SiC) based high temperature semiconductor gas sensors were tested for potential applications in the closed-loop control of NOx storage catalytic converters. The exhaust gas composition behind a storage catalyst was simulated by synthetic gas mixtures supplied from a gas blending manifold. In lean oxidizing ambients the sensors produced signals opposite in sign upon the appearance of NOx on the one hand and mixtures of HC and CO on the other hand. Transient gas measurements revealed response times ranging between several milliseconds for HC and several seconds for NOx. These features render SiC based sensors potentially useful for the control of NOx storage catalytic converters.

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.

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.

Sheet metal stamping involves a system of complex tribological (friction, lubrication, and wear), heat transfer, and material strain interactions. Accurate coefficient of friction, strain, and lubrication regime data is required to allow proper modeling of the various sheet stamping processes. In addition, non-intrusive means of monitoring the coefficient of friction in production stamping operations would be of assistance for efficiently maintaining proper stamping quality and to indicate when adjustments to the various stamping parameters, including maintenance, would be advantageous. One of the key sub-systems of the sheet metal stamping process is the draw bead. This paper presents an investigation of the tribology of the draw bead using a Draw Bead Simulator (DBS) Machine and automotive zinc-coated sheet steels. The investigation and findings include: 1) A new, non-intrusive method of measuring the surface temperature of the sheet steel as it passes through the draw bead.

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.

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.

Novel testing procedures and analytical methodologies to assess the performance of hybrid electric vehicle batteries have been developed. Tests include both characterization and cycle life and/or calendar life, and have been designed for both Power Assist and Dual Mode applications. Analytical procedures include a battery scaling methodology, the calculation of pulse resistance, pulse power, available energy, and differential capacity, and the modeling of calendar- and cycle-life data. Representative performance data and examples of the application of the analytical methodologies including resistance growth, power fade, and cycle- and calendar-life modeling for hybrid electric vehicle batteries are presented.

The recent trends of increasing driveline torque and use of traction control devices call for increasingly higher durability capacity from driveline components. Bench and vehicle durability tests are often used to validate designs, but they are not cost-effective and take months to complete. Traditional finite element analysis (FEA) procedures have been used effectively in the re-design of driveline components to reduce stress, and occasionally, to predict fatigue life. But in the case of certain rotating components, such as the Axle Differential Case, where the component sees large stress/strain fluctuations within the course of one complete rotation, even under constant input torque, historical fatigue analysis (when conducted) yields very conservative results. The axle differential case tends to be one of the weakest links in the rear axle assembly. Therefore, there is a crucial need for analytical methods to more accurately predict fatigue life to reduce testing time and cost.

The effect of forming strains on the fatigue behavior of an automotive mild steel, interstitial free steel, was studied after being prestrained by balanced biaxial stretch and plane strain. In the long life region, higher than 5×105 reversals, prestrain improves fatigue resistance. In the short life region, prestrain reduces fatigue resistance. At even shorter fatigue lives, the detrimental effect of prestrain diminishes. For plane strains, the fatigue behavior is anisotropic. In the direction perpendicular to the major strain, the steel exhibits much better fatigue resistance than in the direction parallel to the major strain.

The response of the spine acceleration to rib and pelvis acceleration input of the side impact dummy (SID) is modeled using system identification methods. The basis for the modeling is a simplified representation of the SID by a 3-mass, 2-spring system. Based on this spring-mass representation, two types of response models are established. The first is a "gray-box" type with rib/pelvis-spine relationship modeled by Auto Regression with eXogeneous (or eXtra) input (ARX) type system models. The structure of these models is partially based on the spring-mass simplified representation, hence the notion "gray- box." The parameters of these models are identified through linear regression from test data. The second type of models is noted "physical model" here, since it is strictly a state- space form of the equation of motion of the simple spring-mass representation.