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Many efficient modeling methods have been developed for analyzing the effects of component-level variations and uncertainties on the system-level response of complex structures. However, relatively little work has addressed the efficient or agile modeling of variations in the connections between components. Such a capability would be useful for simulation (e.g., performing reliability analysis accounting for spot welding variations) and design (e.g., determining fastener locations for up-armor kits) of commercial and military ground vehicle structures. In this work, a component mode synthesis approach to structural modeling is enhanced by also modeling variations in the connections between components. With this framework, changes in the joining or fastening of the components can be considered in a structural analysis or design process. The components are condensed statically or dynamically with all the candidate joining nodes being retained as active degrees of freedom.

A unique concept for a multi-body test rig enabling the simulation of longitudinal, steering and vertical dynamics was developed at the Institute for Mechatronic Systems (IMS) at TU Darmstadt. A prototype of this IMS test rig is currently being built. In conjunction with the IMS test rig, the Vehicle Terrain Performance Laboratory (VTPL) at Virginia Tech further developed a full car, seven degree of freedom (7 DOF) simulation model capable of accurately reproducing measured displacement, pitch, and roll of the vehicle body due to terrain excitation. The results of the 7 DOF car model were used as the reference input to the multi-body IMS test rig model. The goal of the IMS/VTPL joint effort was to determine whether or not a controller for the IMS test rig vertical actuator could accurately reproduce wheel displacements due to different measured terrain constraints.

Currently, the final stages of chassis development are conducted on prototype vehicles, requiring vehicle manufacturers to dedicate copious resources to the development of each new vehicle platform. The objective of this work is to provide development engineers a system identification tool enabling them to use modeling and simulation to better estimate the required vehicle system parameters. This work develops a parameter identification method for existing vehicle models in which measured terrain data is used as the model excitation. The model was validated using a variety of excitation events and shown to provide accurate estimations of a vehicle’s roll, pitch, and vertical displacement.

This paper presents the utilization of alternative correlation functions in the Kriging method for generating surrogate models (metamodels) for the performance of the bearings in an internal combustion engine. Originally, in the Kriging method an anisotropic exponential covariance function is developed by selecting optimal correlation parameters through optimization. In this paper an alternative nonparametric isotropic covariance approach is employed instead for generating the correlation functions. In this manner the covariance for spatial data is evaluated in a more straightforward manner. The metamodels are developed based on results from a simulation solver computed at a limited number of sample points, which sample the design space.

The utilization of commercially based technologies has the ability to greatly reduce the time and cost of military vehicle development. Commercially based technologies also enable the transition of a high level of capability into the military vehicle inventory and to the Army's ultimate customer, the soldier. The Army's National Automotive Center (NAC) has created SmarTruck, a light truck platform enhanced for military concept exploration. SmarTruck is outfitted with telematics, safety, and non-lethal weapon systems technology. It is a prime example of the NAC's central focus, which is dual-use commercial technology transfer. At the core of success for SmarTruck is the application of telematics technologies including embedded diagnostics, advanced electronic architectures, tele-maintenance, and wireless communications.

A high fidelity seat suspension model, which can be used for ride quality predictions, is developed in this work. The coil-spring seat suspension model includes unique nonlinear forms for the stiffness and damping characteristics. This is the first paper to consider the nonlinear geometric effects of the suspension, derive the coil-spring suspension model from physical principles, and compare theoretical and experimental results. A simplified nonlinear form is achieved via an admissible function describing the vertical suspension deflection as a function of the lateral position. This simplified nonlinear form is compared to experimental data and demonstrated to have exceptional fidelity.

Load data representing severe customer usage is required during the chassis development process. The use of road profiles and vehicle models to predict chassis loads is currently being researched; this research hinges on the ability to accurately measure road profiles. This work focuses on detecting possible signal defects such as leaves on the ground, reflecting surfaces, or narrow roadway gaps. The objective of this work is to develop a simulation procedure that checks the measured road profile for plausibility. The position of the vehicle body is recorded as part of the typical road profiling process. Ideally, a mathematical model can predict the body position from a road profile. The first step in verifying the plausibility of road profiles is to predict the body position. Next, the measured body position is compared to the predicted body position for the road profile in question. New criteria for plausibility checking are a major contribution of this work.

The accuracy of computer-based ground vehicle durability and ride quality simulations depends on accurate representation of road surface topology as vehicle excitation data since most of the excitation exerted on a vehicle as it traverses terrain is provided by the terrain topology. It is currently not efficient to obtain accurate terrain profile data of sufficient length to simulate the vehicle being driven over long distances. Hence, durability and ride quality evaluations of a vehicle depend mostly on data collected from physical tests. Such tests are both time consuming and expensive, and can only be performed near the end of a vehicle's design cycle. This paper covers the development of a methodology to synthesize terrain profile data based on the statistical analysis of physically measured terrain profile data.

The U.S. Army uses the root mean squared of elevation, or the RMSE standard for characterizing road/off-road roughness descriptions. This standard has often appeared in contracts as a performance requirement for the vehicle system. One important application of the standard is describing the testing environment for the vehicle. A physical test, which uses the standard, is the 30,000 mile endurance test. More recently, another metric has been used, the power spectral density (PSD) of road roughness. The international standard for road roughness is known as the International Roughness Index (IRI), and all road construction projects in the U.S. are based on this, as well as Department of Transportation analyses. This paper will analyze the different standards by comparing and contrasting the various aspects of each. Depending on the standard and metrics chosen, the simulation results will have different correlations with actual test.

The U.S. Army uses the root mean square and power spectral density of elevation to characterize road/terrain (off-road) roughness for durability. This paper describes research aimed toward improving these metrics. The focus is on taking previously developed metrics and applying them to mathematically generated terrains to determine how each metric discerns the relative roughness of the terrains from a vehicle durability perspective. Multiple terrains for each roughness level were evaluated to determine the variability for each terrain rating metric. One method currently under consideration is running a relatively simple, yet vehicle class specific, model over a given terrain and using predicted vehicle response(s) to classify or characterize the terrain.

Standard visual database modeling practices in driving simulation reduce geometric complexity of terrain surfaces by using texture maps to simulate high frequency detail. Typically the vehicle dynamics model queries a correlated database that contains the polygons from the high level of detail of the visual database. However the vehicle dynamics database does not contain any of the high frequency information included in the texture maps. To overcome this issue and enhance both the visual and vehicle dynamics databases, a mathematical model of the high frequency content of the ground surface is developed using a set of Non-Uniform Rational B-Splines (NURBS) patches. The patches are combined in the terrain query by superimposing them over the low-frequency polygonal terrain, reintroducing the missing content. The patches are also used to generate Bump Map textures for the image generator so that the visual representation matches the terrain query.

The U.S. Army uses the root mean square and power spectral density of elevation to characterize road/terrain (off-road) roughness for durability. This paper describes research aimed toward improving these metrics. The focus is on taking previously developed metrics and applying them to mathematically generated terrains to determine how each metric discerns the relative roughness of the terrains from a vehicle durability perspective. Multiple terrains for each roughness level were evaluated to determine the variability for each terrain rating metric. One method currently under consideration is running a relatively simple, yet vehicle class specific, model over a given terrain and using predicted vehicle response(s) to classify or characterize the terrain.

The 21st Century Truck Initiative represents the premier partnership between government (Departments of Defense, Army, Energy, Transportation and the Environmental Protection Agency) and the U.S. trucking and supporting industries in seeking to develop and demonstrate commercially viable advanced technologies for trucks in the 21st century. At the request of senior leadership within the U.S. Departments of Defense and the Army, the Tank-automotive and Armaments Command's (TACOM) National Automotive Center (NAC), located at TACOM's Tank-Automotive Research, Development & Engineering Center (TARDEC), spearheaded the creation of this government-industry partnership to pursue the necessary leap-ahead technologies. By teaming the research and development efforts of government and industry, the partnership will improve fuel efficiency, increase safety, reduce owning and operating costs, and reduce emissions, while maintaining or enhancing the performance of military and commercial trucks.

This paper will describe the Army's Vehicle Intelligence Program and discuss some of the VI technologies being considered for use within the Army's Tactical Wheeled Vehicle fleet. It will describe some initial modeling efforts that focus on the fuel efficiency impacts of selected VI technologies and will suggest the impacts of an integrated and networked fleet with regard to logistics. Lastly, it will identify several areas of AVIP research that are being considered in the near term. All of these programs impact directly on the 21st Century (21T) Truck program. [1]

Computationally efficient tire models are needed to meet the timing and accuracy demands of the iterative vehicle design process. Axisymmetric, circumferentially isotropic, planar, discretized models defined by their quasi-static constraint modes have been proposed that are parameterized by a single stiffness parameter and two shape parameters. These models predict the deformed shape independently from the overall tire stiffness and the forces acting on the tire, but the parameterization of these models is not well defined. This work develops an admissible domain of the shape parameters based on the deformation limitations of a physical tire, such that the tire stiffness properties cannot be negative, the deformed shape of the tire under quasi-static loading cannot be dominated by a single harmonic, and the low spatial frequency components must contribute more than higher frequency components to the overall tire shape.

The vertical force generated from terrain-tire interaction has long been of interest for vehicle dynamic simulations and chassis development. To improve simulation efficiency while still providing reliable load prediction, a terrain pre-filtering technique using a constraint mode tire model is developed. The wheel is assumed to convey one quarter of the vehicle load constantly. At each location along the tire's path, the wheel center height is adjusted until the spindle load reaches the pre-designated load. The resultant vertical trajectory of the wheel center can be used as an equivalent terrain profile input to a simplified tire model. During iterative simulations, the filtered terrain profile, coupled with a simple point follower tire model is used to predict the spindle force. The same vehicle dynamic simulation system coupled with constraint mode tire model is built to generate reference forces.