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Torsional stiffness properties were developed for both a 53-foot box trailer and a 28-foot flatbed control trailer based on experimental measurements. In order to study the effect of torsional stiffness on the dynamics of a heavy truck vehicle dynamics computer model, static maneuvers were conducted comparing different torsional stiffness values to the original rigid vehicle model. Stiffness properties were first developed for a truck tractor model. It was found that the incorporation of a torsional stiffness model had only a minor effect on the overall tractor response for steady-state maneuvers up to 0.4 g lateral acceleration. The effect of torsional stiffness was also studied for the trailer portion of the existing model.

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.

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).

The paper discusses the development of a model for the 2006 BMW 330i for the National Advanced Driving Simulator's (NADS) vehicle dynamics simulation, NADSdyna. The front and rear suspensions are independent strut and link type suspensions modeled using recursive rigid-body dynamics formulations. The suspension springs and shock absorbers are modeled as force elements. The paper includes parameters for front and rear semi-empirical tire models used with NADSdyna. Longitudinal and lateral tire force plots are also included. The NADSdyna model provides state-of-the-art high-fidelity handling dynamics for real-time hardware-in-the-loop simulation. The realism of a particular model depends heavily on how the parameters are obtained from the actual physical system. Complex models do not guarantee high fidelity if the parameters used were not properly measured. Methodologies for determining the parameters are detailed in this paper.

This research focuses on the development and performance of analytical models to simulate a tractor-semitrailer in straight-ahead braking. The simulations were modified and tuned to simulate full-treadle braking with all brakes functioning correctly, as well as the behavior of the tractor-semitrailer rig under full braking with selected brakes disabled. The models were constructed in TruckSim and based on a tractor-semitrailer used in dry braking performance testing. The full-scale vehicle braking research was designed to define limits for engineering estimates on stopping distance when Class 8 air-braked vehicles experience partial degradation of the foundation brake system. In the full scale testing, stops were conducted from 30 mph and 60 mph, with the combination loaded to 80,000 lbs (gross combined weight or GCW), half payload, and with the tractor-semitrailer unladen (lightly loaded vehicle weight, or LLVW).

This paper describes a method to evaluate vehicle stability and controllability when the vehicle operates in the nonlinear range of lateral dynamics. The method is applied to open-loop steering maneuvers as well as closed-loop path-following maneuvers. Although path-following maneuvers are more representative of real world driving intent, they are usually considered inappropriate for objective assessment because of repeatability and accuracy issues. The automated test driver (ATD) can perform path-following maneuvers accurately and with good repeatability. This paper discusses the usefulness of application of the automated test drivers and path-following maneuvers. The dynamic mode of instability is not directly obtained from measurable outputs such as yawrate and lateral acceleration as in open-loop maneuvers. A few metrics are defined to quantify deviation from desired or ideal behavior in terms of observed “unexpected” lateral force and moment.

This paper presents the details of the model for the physical steering system used on the National Advanced Driving Simulator. The system is basically a hardware-in-the-loop (steering feedback motor and controls) steering system coupled with the core vehicle dynamics of the simulator. The system's torque control uses cascaded position and velocity feedback and is controlled to provide steering feedback with variable stiffness and dynamic properties. The reference model, which calculates the desired value of the torque, is made of power steering torque, damping function torque, torque from tires, locking limit torque, and driver input torque. The model also provides a unique steering dead-band function that is important for on-center feel. A Simulink model of the hardware/software is presented and analysis of the simulator steering system is provided.

This paper presents an evaluation of a complete vehicle dynamics model for a 1998 Chevrolet Malibu to be used for the National Advanced Driving Simulator. Vehicle handling, braking and powertrain dynamics are evaluated and simulation results are compared with experimental field-testing. NADSdyna, the National Advanced Driving Simulator vehicle dynamics software, is used. The Malibu evaluation covers vehicle directional dynamics that include steady state, transient frequency response, and vehicle longitudinal dynamics composed of acceleration and braking. Also, analyses of the effects of modified tire parameters on vehicle dynamics response is performed. The effects of wind gusts generated by a tractor-trailer and a bus on the Malibu vehicle directional dynamics are analyzed. For the steering system feel, we compare the handwheel torque feedback with the measured data during both high-speed dynamics and in the very low speed tire stick-slip regime.

The paper discusses the development of a model for a 1998 Chevrolet Malibu for the National Advanced Driving Simulator’s (NADS) vehicle dynamics simulation, NADSdyna. The Malibu is the third vehicle modeled for the NADS, and this is the third paper dealing with model development. SAE Paper 970564 contains details of the model for the 1994 Ford Taurus and SAE Paper 1999–01-0121 contains details of the model for the 1997 Jeep Cherokee. The front and rear suspensions are independent strut and link type suspensions modeled using recursive rigid body dynamics formulations. The suspension springs and shock absorbers are modeled as elements in the rigid body formulation. To complement the vehicle dynamics for the NADS application, subsystem models that include tire forces, braking, powertrain, aerodynamics, and steering are added to the rigid body dynamics model. The models provide state-of-the-art high fidelity vehicle handling dynamics for real-time simulation.

The widely used Extended Kalman Filter (EKF) is applied to a planar model of an articulated vehicle to predict jackknifing events. The states of hitch angle and hitch angle rate are estimated using a vehicle model and the available or “measured” states of lateral acceleration and yaw rate from the prime mover. Tuning, performance, and compromises for the EKF in this application are discussed. This application of the EKF is effective in predicting the onset of instability for an articulated vehicle under low-μ and low-load conditions. These conditions have been shown to be most likely to render heavy articulated vehicles vulnerable to jackknife instability. Options for model refinements are also presented.

This paper presents a real-time steering system torque feedback model used in the National Advanced Driving Simulator (NADS). The vehicle model is based on real-time recursive multi-body dynamics augmented with vehicle subsystems models including tires, power train, brakes, aerodynamics and steering. The steering system feel is of paramount importance for the fidelity of the simulator. The driver has to feel the appropriate torque as he/she steers the vehicle. This paper presents a detailed mathematical model of the steering physics from low-speed stick-slip to high-speed states. On-center steering weave handling and aggressive lane change inputs are used to validate the basic mathematical predictions. This validation is objective and open loop, and was done using field experiments.

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.

This paper presents the development of a real-time vehicle dynamics model of the heavy tractor-trailer combination used in the National Advanced Driving Simulator. The model includes multi-body dynamics of the tractor and trailer chassis, suspension, and steering mechanisms. The rigid body model is formulated using recursive multi-body dynamics code. This model is augmented with subsystem models that include tires, leaf springs, brakes, steering system, and aerodynamic drag. This paper also presents parameter measurement and estimations used to set up the model. Also included are models for brake fade, steering torque resistance, and defective tires.

This paper evaluates the heavy tractor-trailer handling dynamics model used in the National Advanced Driving Simulator. The comparison between simulation and experiments were done using lane change, slowly increasing steer, pulse steer, step steer, and straight-line braking maneuvers. The paper discusses tractor-trailer instrumentation and the results of field experiments.

The goal of this research was to find vehicle characteristics which may contribute to steering maneuver induced rollover accidents. This work involved studying vehicle handling dynamics using the Vehicle Dynamics Analysis, Non-Linear (VDANL) computer simulation. The simulation was used to predict vehicle responses while performing 28 different steering induced maneuvers for each of 51 vehicles. Various measures of vehicle response (metrics), such as response times, percent overshoots, etc., were computed for each vehicle from simulation predictions. These vehicle directional response metrics were analyzed in an attempt to identify vehicle characteristics that might be good predictor/explanatory variables for vehicle rollover propensity. The metrics were correlated, using the Statistical Analysis System (SAS) software and logistic regression, with single vehicle accident data from the state of Michigan for the years 1986 through 1988.

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.

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 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.

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.