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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 research was to model a 6×4 tractor-trailer rig using TruckSim and simulate severe braking maneuvers with hardware in the loop and software in the loop simulations. For the hardware in the loop simulation (HIL), the tractor model was integrated with a 4s4m anti-lock braking system (ABS) and straight line braking tests were conducted. In developing the model, over 100 vehicle parameters were acquired from a real production tractor and entered into TruckSim. For the HIL simulation, the hardware consisted of a 4s4m ABS braking system with six brake chambers, four modulators, a treadle and an electronic control unit (ECU). A dSPACE simulator was used as the “interface” between the TruckSim computer model and the hardware.

The (Vehicle Inertia Parameter Evaluation Rig) VIPER II is a full vehicle mass and inertia parameter measurement machine. The VIPER II expands upon the capabilities of its predecessor and is capable of measuring vehicles with a mass of up to 45,360 kg (100,000 lb), an increase in capacity of 18,100 kg (40,000 lb). The VIPER II also exceeds its predecessor in both the length and width of vehicles it can measure. The VIPER II's maximum vehicle width is 381 cm (150 in) an increase of 76 cm (30 in) and maximum distance from the vehicle CG to the outer most axle is 648 cm (255 in) an additional 152 cm (60 in) The VIPER II is capable of performing measurements including vehicle CG height, pitch, roll, and yaw moments of inertia and the roll/yaw cross product of inertia. While being able to measure both heavier and larger vehicles, the VIPER II is designed to maintain a maximum error of 3% for all inertia measurements and 1% for CG height.

The tractor trailer models discussed in this paper were for a real-time hardware-in-the-loop (HIL) simulation to test heavy truck electronic stability control (ESC) systems [1]. The accuracy of the simulation results relies on the fidelity and accuracy of the vehicle parameters used. However in this case where hardware components are part of the simulation, their accuracy also affects the proper working of the simulation and ESC unit. Hence both the software and hardware components have to be validated. The validation process discussed in this paper is divided into two sections. The first section deals with the validation of the TruckSim vehicle model, where experimental data is compared with simulation results from TruckSim. Once the vehicle models are validated, they are incorporated in the HIL simulation and the second section discusses the validation of the whole HIL system with ESC.

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.

In 2004, a model of a 6s6m ABS controller was developed in order to support NHTSA's efforts in the study of heavy truck braking performance. This model was developed using Simulink and interfaced with TruckSim, a vehicle dynamics software package, in order to create an accurate braking simulation of a 6×4 Peterbilt straight truck. For this study, the vehicle model braking dynamics were improved and the ABS controller model was refined. Also, the controller was made adaptable to ABS configurations other than 6s6m, such as 4s4m and 4s3m. Controller models were finally validated to experimental data from the Peterbilt truck, gathered at NHTSA's Vehicle Research and Test Center (VRTC).

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 describes the development and implementation of an accurate and repeatable path-following algorithm focused ultimately on vehicle testing. A compact, lightweight, and portable hardware package allows easy installation and negligible impact on the vehicle mass, even for the smallest automobile. Innovative features include the ability to generate a smooth, evenly-spaced path vector regardless the quality of the given path. The algorithm proposed in this work is suitable for testing in a controlled environment. The system was evaluated in simulation and performed well in road tests at low speeds.

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.

The paper discusses the development of a vehicle dynamics model and model validation of the 2003 Ford Expedition in CarSim. The accuracy of results obtained from simulations depends on the realism of the model which in turn depends on the measured data used to define the model parameters. The paper describes the tests used to measure the vehicle data and also gives a detailed account of the methodology used to determine parameters for the CarSim Ford Expedition model. The vehicle model was validated by comparing simulation results with experimental testing. Bounce and Roll tests in CarSim were used to validate the suspension and steering kinematics and compliances. Field test data of the Sine with Dwell maneuver was used for the vehicle model validation. The paper also discusses the development of a functional electronic stability control system and its effect on vehicle handling response in the Sine with Dwell maneuver.

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).

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 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.

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.

This study investigated the jackknife stability of Class VIII double tractor-trailer combination vehicles that had mixed braking configurations between the tractor and trailers and dolly (e.g. ECBS disc brakes on the tractor and pneumatic drum brakes on the trailers and dolly). Brake-in-turn maneuvers were performed with varying vehicle loads and surface conditions. Conditions with ABS ON for the entire vehicle (and select-high control algorithm on the trailers and dolly) found that instabilities (i.e. lane excursions and/or jackknifes) were exhibited under conditions when the surface friction coefficient was 0.3. It was demonstrated that these instabilities could be avoided while utilizing a select-low control algorithm on the trailers and dolly. Simulation results with the ABS OFF for the tractor showed that a tractor equipped with disc brakes had greater jackknife stability.

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.

This paper discusses the derivation and validation of planar models of articulated vehicles that were developed to analyze jackknife stability on low-μ surfaces. The equations of motion are rigorously derived using Lagrange's method, then linearized for use in state-space models. The models are verified using TruckSim™, a popular nonlinear solid body vehicle dynamics modeling package. The TruckSim™ models were previously verified using extensive on-vehicle experimental data [1, 2]. A three-axle articulated model is expanded to contain five axles to avoid lumping the parameters for the drive and semitrailer tandems. Compromises inherent in using the linearized models are discussed and evaluated. Finally, a nonlinear tire cornering force model is coupled with the 5-axle model, and its ability to simulate a jackknife event is demonstrated. The model is shown to be valid over a wide range of inputs, up to and including loss of control, on low-and-medium-μ surfaces.

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.