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This study outlines an approach for speeding up the simulation of the dynamic response of vehicle models that include hysteretic nonlinear tire components. The method proposed replaces the hysteretic nonlinear tire model with a surrogate model that emulates the dynamic response of the actual tire. The approach is demonstrated via a dynamic simulation of a quarter vehicle model. In the proposed methodology, training information generated with a reduced number of harmonic excitations is used to construct the tire hysteretic force emulator using a Neural Network (NN) element. The proposed approach has two stages: a learning stage, followed by an embedding of the learned model into the quarter car model. The learning related main challenge stems from the attempt to capture with the NN element the behavior of a hysteretic element whose response depends on its loading history.

This paper presents a computational framework for the physics-based simulation of light vehicles operating on discrete terrain. The focus is on characterizing through simulation the mobility of vehicles that weigh 1000 pounds or less, such as a reconnaissance robot. The terrain is considered to be deformable and is represented as a collection of bodies of spherical shape. The modeling stage relies on a novel formulation of the frictional contact problem that requires at each time step of the numerical simulation the solution of an optimization problem. The proposed computational framework, when run on ubiquitous Graphics Processing Unit (GPU) cards, allows the simulation of systems in which the terrain is represented by more than 0.5 million bodies leading to problems with more than one million degrees of freedom.

The use of virtual prototyping early in the design stage of a product has gained popularity due to reduced cost and time to market. The state of the art in vehicle simulation has reached a level where full vehicles are analyzed through simulation but major difficulties continue to be present in interfacing the vehicle model with accurate powertrain models and in developing adequate formulations for the contact between tire and terrain (specifically, scenarios such as tire sliding on ice and rolling on sand or other very deformable surfaces). The proposed work focuses on developing a ground vehicle simulation capability by combining several third party packages for vehicle simulation, tire simulation, and powertrain simulation. The long-term goal of this project consists in promoting the Digital Car idea through the development of a reliable and robust simulation capability that will enhance the understanding and control of off-road vehicle performance.

This contribution demonstrates the use of high performance computing, specifically Graphics Processing Unit (GPU) based computing, for the simulation of tracked ground vehicles. The work closes a gap in physics based simulation related to the inability to accurately characterize the 3D mobility of tracked vehicles on granular terrains (sand and/or gravel). The problem of tracked vehicle mobility on granular material is approached using a discrete element method that accounts for the interaction between the track and each discrete particle in the terrain. This continuum approach captures the dynamics of systems with more than 1,000,000 bodies interacting simultaneously. Two factors render the approach feasible. First, the frictional contact problem between the terrain and the vehicle draws on a convex optimization methodology in which the solution becomes the first order optimality condition of a cone complementarity problem.

In this paper a yaw stability control algorithm along with an emergency roll control strategy have been developed. The yaw stability controller and emergency roll controller were both developed using linear two degree-of-freedom vehicle models. The yaw stability controller is based on Lyapunov stability criteria and uses vehicle lateral acceleration and yaw rate measurements to calculate the corrective yaw moment required to stabilize the vehicle yaw motion. The corrective yaw moment is then applied by means of a differential braking strategy in which one wheel is selected to be braked with appropriate brake torque applied. The emergency roll control strategy is based on a rollover coefficient related to vehicle static stability factor. The emergency roll control strategy utilizes vehicle lateral acceleration measurements to calculate the roll coefficient. If the roll coefficient exceeds some predetermined threshold value the emergency roll control strategy will deploy.

The U.S. Army Tank Automotive Research Development and Engineering Center (TARDEC) and the U.S. Army Corps of Engineers (USACE) are improving modeling and simulation technologies in order to predict the performance of Army ground platforms with a high degree of confidence. In order to provide a framework within which to evaluate the simulation technologies and provide a measure of the progress of the effort, a suite of virtual test operating procedures are being implemented. This framework is called the Virtual Evaluation Suite (VES). It is applicable to the study of ground vehicle stability, handling, ride, mobility, and durability over all terrains under all weather conditions. Although developed in order to evaluate simulation technologies, the VES may be considered a simulation that could be used to exercise any ground platform model that meets the VES standard vehicle interface.

A Vehicle Dynamics and Mobility Server (VDMS) is being developed by the U.S. Army to perform real-time high-fidelity simulation of robotic vehicle concepts. It allows a set of conceptual Unmanned Ground Vehicles (UGVs) to be selected and configured for the purposes of evaluating their mobility performance in a simulated battlefield scenario. VDMS includes real-time ground vehicle models operating over high-resolution digital terrain. The models consist of three-dimensional multi-body vehicle dynamics, off-road vehicle-soil interaction, collision detection and obstacle negotiation code, and autonomous control algorithms. A minimally completed VDMS was used in an RDEC Federation Calibration Experiment (CalEx) in October 2001 to predict the mobility of ten robotic scout vehicles. This paper presents the rationale, requirements, design, and implementation of VDMS. It also briefly discusses other possible applications of VDMS and the future direction of VDMS.

This paper discusses the development of a novel deformable terrain database and its use in a co-simulation environment with a multibody dynamics vehicle model. The implementation of the model includes a general tire-terrain traction model which is modular to allow for any type of tire model that supports the Standard Tire Interface[1] to operate on the terrain. This allows arbitrarily complex tire geometry to be used, which typically has a large impact on the mobility performance of vehicles operating on deformable terrains. However, this gain in generality comes at the cost that popular analytical pressure-sinkage terramechanics models cannot be used to find the normal pressure and shear stress of the contact patch. Pressure and shear stress are approximated by combining the contributions from tire normal forces, shear stresses and bulldozing forces due to soil rutting.

The purpose of this study is to improve predicted tire forces for vehicle simulations on off-road terrain and for simulations incorporating terrain features such as curbs, pavement markers or potholes. The model presented in this paper describes the longitudinal behavior of the tire for traversing high-fidelity terrain profiles. An extended rolling radial-interradial tire model is used to estimate the pressure distribution of the tire contact patch, while a tangential spring model of the tire carcass is used to estimate tractive forces at the tire/road interface. Due to the complexity of the model real-time simulation is not possible, however it is useful for off-line simulations incorporating rough terrain or short-wavelength terrain features.

A virtual, all-season test site for use in real-time vehicle simulators and mobility models was constructed of an Army firing range in Northern Vermont. The virtual terrain will mimic the terrain of our Virtual Data Acquisition and Test Site (VDATS) at Ethan Allen Firing Range (EAFR). The objective is to realistically simulate on- and off-road vehicle performance in all weather conditions for training and vehicle design for the US Army. To this end, several spatial datasets were needed to accurately map the terrain and estimate the state-of-the-ground and terrain strength at different times of the year. The terrain strength is characterized by terramechanics properties used in algorithms to calculate the forces at the vehicle-terrain interface. The performance of the real vehicles will be compared to the simulated vehicle performance of operator-in-the-loop and unmanned vehicles for validation of the simulations.

In the context of off-road vehicle simulations, deformable terrain models mostly fall into three categories: simple visualization of the deformed terrain only, use of empirical relationships for the deformation, or finite/discrete element approaches for the terrain. A real-time vehicle dynamics simulation with a physics-based tire model (brush, ring or beam-based models) requires a terrain model that accurately reflects the deformation and response of the soil to all possible inputs of the tire in order to correctly simulate the response of the vehicle. The real-time requirement makes complex finite/discrete element approaches unfeasible, and the use of a ring or beam -based tire model excludes purely empirical terrain models. We present the development of a three-dimensional vehicle/terrain interaction model which is comprised of a tire and deformable terrain model to be used with a real-time vehicle dynamics simulator.

In this paper we present a project that interfaced the National Advanced Driving Simulator (NADS) with SynChrono, a module of the Project Chrono open source simulation platform, to enable real-time, physics-based simulation of multiple autonomous vehicles (AVs) interacting with manned vehicles. In this setup, a driver at NADS, at the University of Iowa, participates in a traffic scenario that involves AVs that run at the University of Wisconsin-Madison on a cluster supercomputer. The NADS simulator is a driving simulator giving the “most realistic driving simulation experience in the country” [1]. Thanks to its actuators, it can move across its 64-foot by 64-foot bay, rotate and tilt, to emulate vehicle movement and vibrations. In addition, the human driver drives in a full-size cab, surrounded by LED monitors, resulting in an immersive, high fidelity driving simulation experience.

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.