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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.

Vehicle dynamics models employed in heavy truck simulation often treat the semitrailer as a torsionally rigid member, assuming zero deflection along its longitudinal axis as a moment is applied to its frame. Experimental testing, however, reveals that semitrailers do twist, sometimes enough to precipitate rollover when a rigid trailer may have remained upright. Improving the model by incorporating realistic trailer roll stiffness values can improve assessment of heavy truck dynamics, as well as an increased understanding of the effectiveness of stability control systems in limit handling maneuvers. Torsional stiffness measurements were conducted by the National Highway Traffic Safety Administration (NHTSA) for eight semitrailers of different types, including different length box vans, traditional and spread axle flat beds, and a tanker.

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).

In 2007, a software model of a Roll Stability Control (RSC) system was developed based on test data for a Volvo tractor at NHTSA's Vehicle Research and Test Center (VRTC). This model was designed to simulate the RSC performance of a commercially available Electronic Stability Control (ESC) system. The RSC model was developed in Simulink and integrated with the available braking model (TruckSim) for the truck. The Simulink models were run in parallel with the vehicle dynamics model of a truck in TruckSim. The complete vehicle model including the RSC system model is used to simulate the behavior of the actual truck and determine the capability of the RSC system in preventing rollovers under different conditions. Several simulations were performed to study the behavior of the model developed and to compare its performance with that of an actual test vehicle equipped with RSC.

Validation was performed on an existing heavy truck vehicle dynamics computer model with roll stability control (RSC). The first stage in this validation was to compare the response of the simulated tractor to that of the experimental tractor. By looking at the steady-state gains of the tractor, adjustments were made to the model to more closely match the experimental results. These adjustments included suspension and steering compliances, as well as auxiliary roll moment modifications. Once the validation of the truck tractor was completed for the current configuration, the existing 53-foot box trailer model was added to the vehicle model. The next stage in experimental validation for the current tractor-trailer model was to incorporate suspension compliances and modify the auxiliary roll stiffness to more closely model the experimental response of the vehicle. The final validation stage was to implement some minor modifications to the existing RSC model.

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.

During Phase VI of the National Highway Traffic Safety Administration's (NHTSA) Light Vehicle Rollover Research Program, three of the twenty-six light vehicles tested exhibited significant response asymmetries with respect to left versus right steer maneuvers. This paper investigates possible vehicle asymmetric characteristics and unintended inputs that may cause vehicle asymmetric response. An analysis of the field test data, results from suspension and steering parameter measurements, and a summary of a computer simulation study are also given.

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 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.

This paper will illustrate the development of the modeling of rollover sequences. During the past few years, a lot of research has been focused on the rollover propensity of vehicles. As to what happens after the vehicle rolls over, attention is only paid to occupant kinematics and occupant injury. Some simple questions such as how many rolls in the rollover are not answered unless a rollover test is run. The rollover sequences including roll number, roll speed and roll distance are very important to the accident reconstructionists as well as design engineers. Since the cost for running a rollover test is so high today, it is very economic and time-efficient to obtain the preliminary results from a mathematical model. Roll number and roll distance versus time are to be obtained through the mathematical model which is based on several rollover tests, vehicle inertia parameters, and the Coulomb friction, a non-linear term in the equation.

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.

The National Highway Traffic Safety Administration's Vehicle Research and Test Center (VRTC) plans to evolve the state-of-the-art of steering system modeling for driving simulators with the ultimate goal being the development of a high fidelity steering feel model for the National Advanced Driving Simulator (NADS). The VRTC plans on developing reliable research tools that can be used to determine the necessary features for a steering model that will provide good objective and subjective steering feel. This paper reviews past and continuing work conducted at the VRTC and provides a plan for future work that will achieve this goal.

This paper presents an overview of work performed by the National Highway Traffic Safety Administration's (NHTSA) Vehicle Research and Test Center (VRTC) to test, validate, and improve the planned National Advanced Driving Simulator's (NADS) vehicle dynamics simulation. This vehicle dynamics simulation, called NADSdyna, was developed by the University of Iowa's Center for Computer-Aided Design (CCAD) NADSdyna is based upon CCAD's general purpose, real-time, multi-body dynamics software, referred to as the Real-Time Recursive Dynamics (RTRD), supplemented by vehicle dynamics specific submodules VRTC has “beta tested” NADSdyna, making certain that the software both works as computer code and that it correctly models vehicle dynamics. This paper gives an overview of VRTC's beta test work with NADSdyna. The paper explains the methodology used by VRTC to validate NADSdyna.

The intent of this research is to understand the effects worn dampers have on vehicle stability and safety through dynamic model simulation. Dampers, an integral component of a vehicle's suspension system, play an important role in isolating road disturbances from the driver by controlling the motions of the sprung and unsprung masses. This paper will show that a decrease in damping leads to excessive body motions and a potentially unstable vehicle. The concept of poor damping affecting vehicle stability is well established through linear models. The next step is to extend this concept for non-linear models. This is accomplished through creating a vehicle simulation model and executing several driving maneuvers with various damper characteristics. The damper models used in this study are based on splines representing peak force versus velocity relationships.

An existing tire model was investigated for additional normal load-dependent characteristics to improve the large truck simulations developed by the National Highway Traffic Safety Administration (NHTSA) for the National Advanced Driving Simulator (NADS). Of the existing tire model coefficients, plysteer, lateral friction decay, aligning torque stiffness and normalized longitudinal stiffness were investigated. The findings of the investigation led to improvements in the tire model. The improved model was then applied to TruckSim to compare with the TruckSim table lookup tire model and test data. Additionally, speed-dependent properties for the NADS tire model were investigated (using data from a light truck tire).