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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.

Motion cueing algorithms can improve the perceived realism of a driving simulator, however, data on the effects on driver performance and simulator sickness remain scarce. Two novel motion cueing algorithms varying in concept and complexity were developed for a limited maneuvering workspace, hexapod/Stuart type motion platform. The RideCue algorithm uses a simple swing motion concept while OverTilt Track algorithm uses optimal pre-positioning to account for maneuver characteristics for coordinating tilt adjustments. An experiment was conducted on the US Army Tank Automotive Research, Development and Engineering Center (TARDEC) Ride Motion Simulator (RMS) platform comparing the two novel motion cueing algorithms to a pre-existing algorithm and a no-motion condition.

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.

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 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.

A tire/terrain interaction model is presented to support the dynamic simulation of off-road ground vehicle. The model adopts a semi-empirical approach that is based on curve fits of soil data combined with soil mechanics theories to capture soil compaction, soil shear deformation, and soil passive failure that associate with off-road driving. The resulting model allows the computation of the tire forces caused by terrain deformation in longitudinal and lateral direction. This model has been compared with experimental data and shown reasonable prediction of the tire/terrain interaction.

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.

Vehicle handling and stability are significantly affected by inertial properties including moments of inertia and center of gravity location. This paper will present an analysis of the NHTSA Inertia Database and give regression equations that approximate moments of inertia and center of gravity height given basic vehicle properties including weight, width, length and height. The handling and stability consequences of the relationships of inertial properties with vehicle size will be analyzed in terms of previously published vehicle dynamics models, and through the use of a nonlinear maneuvering simulation.

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.

This paper describes the driver/vehicle modeling aspects of a computer simulation that can respond to highway engineering descriptions of roadways. The driver model interacts with a complete vehicle dynamics model that has been described previously. The roadway path is described in terms of horizontal and vertical curvature and cross slopes of lanes, shoulders, side slopes and ditches. Terrain queries are made by the vehicle dynamics to locate tires on the roadway cross-section, and to define vehicle path and road curvature at some distance down the road. The driver model controls steering to maintain lateral lane position. Speed is maintained at a speed limit on tangents, and decreased as needed to maintain safe lateral acceleration. Because the bandwidth of longitudinal (speed) control is much lower than lateral/directional (steering) control, the driver model looks further ahead for speed control than for steering.

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]

This paper reviews the development and application of a computer simulation for simulating ground vehicle dynamics including steady state tire behavior. The models have been developed over the last decade, and include treatment of sprung and unsprung masses, suspension characteristics and composite road plane tire forces. The models have been applied to single unit passenger cars, trucks and buses, and articulated tractor/trailer vehicles. The vehicle model uses composite parameters that are relatively easy to measure. The tire model responds to normal load, camber angle and composite tire patch slip, and its longitudinal and lateral forces interact with an equivalent friction ellipse formulation. The tire model can represent behavior on both paved and off-road surfaces. Tire model parameters can be automatically identified given tire force and moment test data.

Handling and stability problems are typically revealed under limit performance maneuvering conditions where tires are pushed to high slip angles under high normal loading conditions. This paper reviews vehicle dynamics handling and stability models relative to tire characteristics and examines tire testing data obtained under normal and extreme maneuvering conditions. Tire data is normalized according to design characteristics in order to reveal basic maneuvering behavior that is relatively independent of size and construction. Computer simulation analysis is used to demonstrate the influence of tire characteristics on handling and stability.

Dynamic stability is influenced by vehicle and tire characteristics and operating conditions, including speed and control inputs. Under limit performance operating conditions, maneuvering can force a vehicle into oversteer and high sideslip. The high sideslip results in limit cornering conditions, which might proceed to spinout, or result in tip-up and rollover. Oversteer and spinout result from rear axle tire side force saturation. Tip-up and rollover occur when tire side forces are sufficient to induce lateral acceleration that will overcome the stabilizing moment of vehicle weight. With the use of computer simulation and generic vehicle designs, this paper explores the vehicle and tire characteristics and maneuvering conditions that lead to loss of directional control and potential tip-up and rollover.

This paper describes a low cost, PC based driving simulation that includes a complete vehicle dynamics model (VDM), photo realistic visual display, torque feedback for steering feel and realistic sound generation. The VDM runs in real-time on Intel based PCs. The model, referred to as VDANL (Vehicle Dynamics Analysis, Non-Linear) has been developed and validated for a range of vehicles over the last decade and has been previously used for computer simulation analysis. The model's lateral and longitudinal dynamics have 17 degrees of freedom for a single unit vehicle and 33 degrees of freedom for an articulated vehicle. The model also includes a complete drive train including engine, transmission and front and rear drive differentials, and complete, power assisted braking and steering systems. A comprehensive tire model (STIREMOD) generates lateral and longitudinal forces and aligning torque based on normal load, camber angle and horizontal (lateral and longitudinal) slip.

Interactive driving simulation is attractive for a variety of applications, including screening, training and licensing, due to considerations of safety, control and repeatability. However, widespread dissemination of these applications will require modest cost simulator systems. Low cost simulation is possible given the application of PC level technology, which is capable of providing reasonable fidelity in visual, auditory and control feel cuing. This paper describes a PC based simulation with high fidelity vehicle dynamics, which provides an easily programmable visual data base and performance measurement system, and good fidelity auditory and steering torque feel cuing. This simulation has been used in a variety of applications including screening truck drivers for the effects of fatigue, research on real time monitoring for driver drowsiness and measurement of the interference effect of in-vehicle IVHS tasks on driving performance.

The physical forces applied to vehicle inertial dynamics derive primarily from the tires. These forces have a profound effect on handling. Tire force modeling therefore provides a critical foundation for overall vehicle dynamics simulation. This paper will describe the role tire characteristics play in handling, and will discuss modeling requirements for appropriately simulating these effects. Tire input and output variables will be considered in terms of their relationship to vehicle handling. General computational requirements will be discussed. An example tire model will be described that allows for efficient computational procedures and provides responses over the full range of vehicle maneuvering conditions.

Computer simulation and real-time, interactive approaches for analysis, interactive driving simulation, and hardware-in-the-loop testing are finding increasing application in the research and development of advanced automotive concepts, highway design, etc. Vehicle dynamics models serve a variety of purposes in simulation. A model must have sufficient complexity for a given application but should not be overly complicated. In interactive driving simulation, vehicle dynamics models must provide appropriate computation for sensory feedback such as visual, motion, auditory, and proprioceptive cuing. In stability and handling simulations, various modes must be properly represented, including lateral/directional and longitudinal degrees of freedom. Limit performance effects of tire saturation that lead to plow out, spin out, and skidding require adequate tire force response models.