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The paper discusses the development of a model of the 2003 Ford Expedition using ADAMS View and its validation with experimental data. The front and rear suspensions are independent double A-arm type suspensions modeled using rigid links and ideal joints. The suspension springs and shock absorbers are modeled as force elements. The plots comparing the experimental tests and the simulation results are shown in this paper. Quasi-static roll and bounce tests are used to validate the suspension characteristics of the model while the Sine with Dwell and Slowly Increasing Steer maneuvers are used to validate the vehicle handling and tire-road interaction characteristics of the model. This paper also details the incorporation of an ESC model, originally developed by Kinjawadekar et al. [2] for CarSim, with the ADAMS model. The ESC is modeled in Simulink and co-simulated with the ADAMS vehicle model. Plots validating the ESC model with experimental data are also included.

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.

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.

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.

A test procedure that rates brake performance must control variability so that measured differences between vehicles are real. Tests were conducted using standard brake test procedures with three drivers in three cars on wet and dry asphalt with the ABS working and disabled. The differences between vehicles were greater than differences due to ABS condition, surface condition, and drivers. The procedure measured differences between all the vehicles with statistical certainty but used many replications and drivers. If only large differences in performance need to be distinguished, fewer replications and drivers will be needed.