Search Results

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.

This paper describes the design and implementation of the SEA, Ltd. Brake and Throttle Robot (BTR). Presented are the criteria used in the initial design and the development and testing of the BTR, as well as some test results achieved with the device. The BTR is designed for use in automobiles and light trucks. It is based on a servomotor driven ballscrew, which in turn operates either the brake or accelerator. It is easily portable from one vehicle to another and compact enough to fit even smaller vehicles. The BTR is light enough so as to have minimal effect on the measurement of vehicle parameters. The BTR is designed for use as a stand-alone unit or as part of a larger control system such as the Automated Test Driver (ATD) yet allows for the use of a test driver for safety, as well as test selection, initiation, and monitoring. Installation in a vehicle will be described, as well as electronic components that support the BTR.

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.

Engine control units (ECUs) on heavy trucks have been capable of storing “last stop” or “hard stop” data for some years. These data provide useful information to accident reconstruction personnel. In past studies, these data have been analyzed and compared to higher-resolution on-vehicle data for several heavy trucks and several makes of passenger cars. Previous published studies have been quite helpful in understanding the limitations and/or anomalies associated with these data. This study was designed and executed to add to the technical understanding of heavy truck event data recorders (EDR), specifically data associated with a modern Cummins power plant ECU. Emergency “full-treadle” stops were performed at many combinations of load-speed-surface coefficient conditions. In addition, brake-in-curve tests were performed on wet Jennite for various conditions of disablement of the braking system.

This research paper builds onto the wealth of technical information that has been published in the past by engineers such as Flick, Radlinski, and Heusser. For this paper, the pushrod force versus chamber pressure data published by Heusser are supplemented with data taken from brake chamber types not reported on by Heusser in 1991. The utility of Heusser's braking force relationships is explored and discussed. Finally, a straightforward and robust method for calculating truck braking performance, based on the brake stroke measurements and published heavy truck braking test results, is introduced and compared to full-scale vehicle test data.

This research was performed using a designed experiment to evaluate the loss of dry surface braking performance and stability that could be associated with the disablement of specific brake positions on a tractor-semitrailer. The experiment was intended to supplement and update previous research by Heusser, Radlinski, Flick, and others. It also sought to establish reasonable limits for engineering estimates on stopping performance degradation attributable to partial or complete brake failure of individual S-cam air brakes on a class 8 truck. Stopping tests were conducted from 30 mph and 60 mph, with the combination loaded to GCW (80,000 lb.), half-payload, and with the flatbed semitrailer unladen. Both tractor and semitrailer were equipped with antilock brakes. Along with stopping distance, brake pressures, longitudinal acceleration, road wheel speed, and steering wheel position and effort were also recorded.

Automating road vehicle control can increase the range and reliability of dynamic testing. Some tests, for instance, specify precise steering inputs which human test drivers are only able to approximate, adding uncertainty to the test results. An automated steering system has been developed which is capable of removing these limitations. This system enables any production car or light truck to follow a user-defined path, using global position feedback, or to perform specific steering sequences with excellent repeatability. The system adapts itself to a given vehicle s handling characteristics, and it can be installed and uninstalled quickly without damage or permanent modification to the vehicle.

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 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.

The shape of an acceleration pulse in an impact is not only affected by the change in velocity, but also by the geometry and stiffness of the both the striking vehicle and the struck object. In this paper, the frontal crash performance of a full-size pickup is studied through a series of impact tests with a rigid pole and with a flat barrier. Each rigid pole test is conducted at one of four locations across the front of the vehicle and at impact speeds of 10 mph, 20 mph, or 30 mph. The flat barrier tests are conducted at 10 mph, 15 mph, 20 mph, and 30 mph. The vehicle crush and acceleration pulses resulting from the pole tests are compared to those resulting from the barrier tests. The severity of pole impacts and the severity of flat barrier impacts are compared based on peak accelerations and pulse durations of the occupant compartment.

There have been a number of papers written about the dynamic effects of low speed front to rear impacts between motor vehicles during the last several years. This has been an important issue in the field of accident analysis and reconstruction because of the frequency with which the accidents occur and the costs of injuries allegedly associated with them. Several of these papers have discussed the importance of the coefficient of restitution in the accelerations and speed changes that the vehicles undergo in such impacts. These discussions often include data showing the measured restitution for impacts involving various bumper types and closing speeds. However, in most of these studies, the impacts are controlled so that direct bumper to bumper impacts occur. This paper will present the results of several rear impact tests with non-standard impact configurations.

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.

This paper introduces a new nonlinear model for simulating the dynamics of pneumatic-over-mechanical commercial vehicle braking systems. The model employs an effective systems approach to accurately reproduce forcing functions experienced at the hubs of heavy commercial vehicles under braking. The model, which includes an on-off type ABS controller, was developed to accurately simulate the steer, drive, and trailer axle drum (or disc) brakes on modern heavy commercial vehicles. This model includes parameters for the pneumatic brake control and operating systems, a 4s/4m (four sensor, four modulator) ABS controller for the tractor, and a 2s/2m ABS controller for the trailer. The dynamics of the pneumatic control (treadle system) are also modeled. Finally, simulation results are compared to experimental data for a variety of conditions.

According to NHTSA's 2011 Traffic Safety Facts [1], passenger vehicle occupant fatalities continued the strong decline that has been occurring recently. In 2011, there were 21,253 passenger vehicles fatalities compared to 22,273 in 2010, and that was a 4.6% decrease. However; large-truck occupant fatalities increased from 530 in 2010 to 635 in 2011, which is a 20% increase. This was a second consecutive year in which large truck fatalities have increased (9% increase from 2009 to 2010). There was also a 15% increase in large truck occupant injuries from 2010. Moreover, the fatal crashes involving large trucks increased by 1.9%, in contrast to other-vehicle-occupant fatalities that declined by 3.6% from 2010. The 2010 accident statistics NHTSA's report reveals that large trucks have a fatal accident involvement rate of 1.22 vehicles per 100 million vehicle miles traveled compared to 1.53 for light trucks and 1.18 for passenger cars.

This paper presents the results of a design space exploration based on the simulations of the MTV (Medium Tactical Vehicle) 5.0 Ton Cargo Truck using MSC-ADAMS (Automatic Dynamic Analysis of Mechanical System). Design space study is conducted using ADAMS/Car and ADAMS/Insight to consider parametric design changes in suspension and the tires of the cargo truck. The methodology uses an industry acknowledged multibody dynamics simulation software (ADAMS) for the modeling of the cargo truck and a flexible optimization architecture to explore the design space. This research is a part of the work done for the U.S. Army TACOM (Tank Automotive and Armaments Command) at the Center for Automotive Research, The Ohio State University.

The severity of an impact in terms of the acceleration in the occupant compartment is dependent not only on the change in vehicle velocity, but also the time for the change in velocity to occur. These depend on the geometry and stiffness of both the striking vehicle and struck object. In narrow-object frontal impacts, impact location can affect the shape and duration of the acceleration pulse that reaches the occupant compartment. In this paper, the frontal impact response of a full-sized pickup to 10 mile per hour and 20 mile per hour pole impacts at the centerline and at a location nearer the frame rails is compared using the acceleration pulse shape, the average acceleration in the occupant compartment, and the residual crush. A bilinear curve relating impact speed to residual crush is developed.

This paper describes an adaptive control strategy for improving the steering response of an automated vehicle steering controller. In order to achieve repeatable dynamic test results, precise steering inputs are necessary. This strategy provides the controller tuning parameters optimized for a particular vehicle's steering system. Having the capability to adaptively tune the steering controller for any vehicle installation provides an easy method for obtaining precise steering inputs for a wide range of vehicles, from small off-road utility vehicles to passenger vehicles to heavy trucks. The S.E.A. Ltd. Automated Steering Controller (ASC) is used exclusively in conducting this research. By recording the torque input to the steering system by the steering controller and the resulting steering angle during only a single test, the ASC is able to characterize the steering system of the test vehicle and create a computer model with appropriate parameters.