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This paper presents a feedback linearization control technique as applied to a Roll Simulator. The purpose of the Roll Simulator is to reproduce in-field rollovers of ROVs and study occupant kinematics in a laboratory setting. For a system with known parameters, non-linear dynamics and trajectories, the feedback linearization algorithm cancels out the non-linearities such that the closed-loop dynamics behave in a linear fashion. The control inputs are computed values that are needed to attain certain desired motions. The computed values are a form of inverse dynamics or feed-forward calculation. With increasing system eigenvalue, the controller exhibits greater response time. This, however, puts a greater demand on the translational actuator. The controller also demonstrates that it is able to compensate for and reject a disturbance in force level.

As part of the evaluation of vehicle simulation models, a vehicle dynamics engineer typically desires to compare simulation results to test data from actual vehicles and/or results from known, or higher fidelity simulations. Depending on the type of model, several types of tests and/or maneuvers may need to be compared. For military vehicles, there is the additional requirement to run specific types of maneuvers for vehicle model evaluations to ensure that the vehicle complies with procurement requirements. A thorough evaluation will run two different categories of tests/maneuvers. The first category consists of laboratory type tests that include weight distribution, kinematics and compliance, steering ratio, and other static measures. The second category consists of dynamic maneuvers that include handling, drive train, braking, ride, and obstacle types. In this paper, a process for proper evaluation of vehicle simulation models is presented.

Typical factors that contribute to the coast down characteristics of a vehicle include aerodynamic drag, gravitational forces due to slope, pumping losses within the engine, frictional losses throughout the powertrain, and tire rolling resistance. When summed together, these reactions yield predictable deceleration values that can be related to vehicle speeds. This paper focuses on vehicle decelerations while coasting with a typical medium-sized SUV. Drag factors can be classified into two categories: (1) those that are caused by environmental factors (wind and slope) and (2) those that are caused by the vehicle (powertrain losses, rolling resistance, and drag into stationary air). The purpose of this paper is to provide data that will help engineers understand and model vehicle response after loss of engine power.

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.

This paper presents a methodology for validating vehicle stability and control computer simulations. Validation is defined as showing that, within some specified operating range of the vehicle, a simulation's predictions of a vehicle's responses agree with the actual measured vehicle's responses to within some specified level of accuracy. The method uses repeated experimental runs at each test condition to generate sufficient data for statistical analyses. The acquisition and reduction of experimental data, and the processing path for simulation data, are described. The usefulness of time domain validation for steady state and slowly varying transients is discussed. The importance of frequency domain validation for thoroughly validating a simulation is shown. Both qualitative and quantitative methods for the comparison of the simulation predictions with the actual test measurements are developed.

This paper describes the development of a more accurate shock absorber model in order to obtain better vehicle simulation results. Previous shock models used a single spline to represent shock force versus shock velocity curves. These models produced errors in vehicle simulations because the damper characteristics are better represented by the application of a hysteresis loop in the model. Thus, a new damper model that includes a hysteresis loop is developed using Matlab Simulink. The damper characteristics for the new model were extracted from measurements made on a shock dynamometer. The new model better represents experimental shock data. The new shock model is incorporated into two different lumped-parameter vehicle models: one is a three degree-of-freedom vehicle handling model and the other is a seven degree-of-freedom vehicle ride model. The new damper model is compared with the previous model for different shock mileages (different degrees of wear).

This paper deals with the ongoing efforts at The Vehicle Research and Test Center (VRTC) in East Liberty, Ohio in promoting the safe operation of heavy trucks. The associated research evaluated two vehicle dynamics simulations for their accuracy in predicting tractor-trailer handling metrics. The goals of the research were threefold: 1. Establish a generic “benchmark” parametric data set for the three-axle truck/two-axle trailer vehicle 2. Demonstrate the accuracy of experimental data that was collected for the tractor-trailer vehicle of this study 3. Demonstrate the accuracy of two vehicle simulations by comparing their predicted responses to experimentally observed vehicle responses and metrics.

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 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.

Computer simulations are popular for modeling vehicle system dynamics. However, further refinement of the vehicle dynamic model is required for extensive use in the automotive industry. In this paper, the model refining procedure is illustrated by developing reliable kinematic models verified with laboratory test results; instrument test data; and a mathematical optimization method. More specifically, simple kinematic models are developed for reduced computation times using ADAMS. They are tuned by the gradient-based optimization technique using the results from a laboratory testing facility, which includes the compliance effect in order to use the kinematic models in dynamic simulations. Also the Magic Formula tire model is developed using the optimization method and tire property data for the STI (Systems Technology, Incorporated) tire model.

The need to measure vehicle parameters required for vehicle dynamics simulations has been a difficult and time-consuming task since the first simulations were developed over 35 years ago. The wide variety of simulations developed have demanded as wide a variety of vehicle parameters. Due in part to this diversity, no standard set of measurement techniques has been developed. A laboratory facility to measure the vehicle parameters for a 13-degree-of-freedom, lumped parameter, nonlinear vehicle dynamics simulation (VDANL) was needed. Parameters for a large number of vehicles were required. Therefore, only a few days could be devoted to measuring the parameters for each vehicle. The Composite Parameter Measurement Device (CPMD) was designed and built to meet these goals. The hardware, data acquisition system and analysis software are presented. The roll test, steer test, and aligning stiffness test, used during the initial testing are discussed.

This paper presents the results of an in-depth study of the measurement of occupant kinematic response on the S-E-A Roll Simulator. This roll simulator was built to provide an accurate and repeatable test procedure for the evaluation of occupant protection and restraint systems during roll events within a variety of occupant compartments. In the present work this roll simulator was utilized for minimum-energy, or threshold type, rollover events of recreational off-highway vehicles (ROVs). Input profiles for these tests were obtained through a separate study involving autonomous full vehicle tests [1]. During simulated roll events anthropomorphic test device (ATD) responses were measured using on-board high speed video, an optical three-dimensional motion capture system (OCMS) and an array of string potentiometers.

Adequacy of resistance spot welds in low carbon steels in relation to structural integrity can become an issue in the reconstruction of automotive accidents. Because formation of a plug (or button or slug) in a peel test is used as a quality control criterion for welds, it is sometimes assumed conversely that a weld which failed is defective if no plug is present. Spot welds do not necessarily form a plug when fractured. Fracture behavior of spot welds both by overload and fatigue is reviewed. Then techniques for examination of field failures are discussed. Finally two case histories are discussed.

For some vehicle dynamics applications, an estimate of a vehicle's center of gravity (cg) height and mass moments of inertia can suffice. For other applications, such as vehicle models and simulations used for vehicle development, these values should be as accurate as possible. This paper presents several topics related to inertial parameter estimation and measurement. The first is a simple but reliable method of estimating vehicle mass moment of inertia values from data such as the center of gravity height, roof height, track width, and other easily measurable values of any light road vehicle. The second is an error analysis showing the effect, during a simple static cg height test, of vehicle motion (relative to the support system) on the vehicle's calculated cg height. A method of accounting for this motion is presented. Similarly, the effects of vehicle motion are analyzed for subsequent mass moment of inertia tests.

This paper presents the development of a tire model for use in the simulation of vehicle dynamics. The model was developed to predict tire lateral and longitudinal force responses to dynamic inputs. In this new tire model, the contact patch of a tire is lumped into a number of elements to study the dynamic behavior of the displacement of the tire contact patch in the lateral and longitudinal directions. For each displacement, a differential equation governing the dynamic behavior of the displacement to the dynamic inputs is derived. Based on the differential equations for the lateral and longitudinal displacements, difference equations are derived for the purpose of simulating tire output responses. Since system parameters, such as mass, damping and stiffness, in the difference equations are unknown, estimation of system parameters is performed using the differential equations and experimental data measured for this research.

The handling, stability, and rollover resistance of vehicles is presently being studied by both the automotive industry and the National Highway and Traffic Safety Administration (NHTSA). However, to study the handling and rollover behavior of each vehicle on the road is not feasible. The ability to categorize and compare the rollover and handling behavior of various vehicles is a subject of considerable research interest. This paper examines the possibility of characterizing vehicle classes through the use of a three degree-of-freedom linear model. Initially, segregation is studied by evaluating the eigenvalue location in the complex domain for vehicle sideslip velocity, yaw rate, and roll angle. Then the influence of numerator dynamics on vehicle behavior is studied and vehicle class segregation is attempted through evaluation of the amplitude ratio of the frequency responses for sideslip velocity, yaw rate, and roll angle.

This paper discusses the development of a 1994 Ford Taurus vehicle model for the National Advanced Driving Simulator's planned vehicle dynamics simulation, NADSdyna. The front and rear suspensions of the Taurus are modeled using recursive rigid body dynamics formulations. To complement vehicle dynamics, subsystems models that include steering, braking, and tire forces are included. These models provide state-of-the-art high fidelity vehicle handling dynamics for real-time simulation. The realism of a particular formulation depend heavily on how the parameters are obtained from the physical system. Therefore, the development of a data set for a particular model is as important as the model itself. The methodology for generating the Taurus data set is presented. The power train model is not yet included, so the simulation is run with the vehicle either at constant speed or decelerating.

This paper presents an evaluation of a vehicle dynamics model intended to be used for the National Advanced Driving Simulator (NADS). Dynamic validation for high performance simulation is not merely a comparison between experimental and simulation plots. It involves strong insight of vehicle's subsystems mechanics, limitations of the mathematical formulations, and experimental predictions. Lateral, longitudinal, and ride dynamics are evaluated using field test data, and analytical diagnostics. The evaluation includes linear and non-linear range of vehicle dynamics response.

As part of the National Advanced Driving Simulator (NADS) program, the Vehicle Research and Test Center (VRTC) in East Liberty, Ohio is evaluating the NADS vehicle dynamics software. As part of VRTC's effort, an extensive vehicle testing program to provide data for the simulation evaluation was performed. This paper describes VRTC's testing of a 1994 Ford Taurus GL passenger car. Each of the test maneuvers run by the Taurus are described, along with instrumentation setup, control actuation, test conditions, and driver procedures. The test data reduction and processing are detailed. Sample results of the testing and an analysis of test repeatability and measurement noise are also presented.

The paper presents an evaluation of two vehicle dynamics simulations: “Vehicle Dynamics Analysis, Non-Linear” (VDANL) from Systems Technology, Inc. and “Vehicle Dynamics Models for Roadway Analysis and Design” (VDM RoAD) from the University of Michigan Transportation Research Institute. The versions of these simulations are being developed for the Federal Highway Administration (FHWA). Working in cooperation with the FHWA, the National Highway Traffic Safety Administration's (NHTSA) Vehicle Research and Test Center (VRTC) in East Liberty, Ohio, has evaluated these simulations. An extensive vehicle parameter measurement and field testing program has been performed using a 1994 Ford Taurus to provide simulation parameters and to “benchmark” data for the simulation evaluation.