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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 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.

A determination of the vehicle states and tire forces is critical to the stability of vehicle dynamic behavior and to designing automotive control systems. Researchers have studied estimation methods for the vehicle state vectors and tire forces. However, the accuracy of the estimation methods is closely related to the employed model. In this paper, tire lag dynamics is introduced in the model. Also application of estimation methods in order to improve the model accuracy is presented. The model is developed by using the global searching algorithm, a Genetic Algorithm, so that the model can be used in the nonlinear range. The extended Kalman filter and sliding mode observer theory are applied to estimate the vehicle state vectors and tire forces. The obtained results are compared with measurements and the outputs from the ADAMS full vehicle model. [15]

This paper discusses the importance of having an adequate model for the dynamic response characteristics of tire lateral force to steering inputs. Computer simulation and comparison with experimental results are used to show the importance of including appropriate tire dynamics in simulation tire models to produce accurate predictions of vehicle dynamics. Improvements made to the tire dynamics model of an existing vehicle stability and control simulation, the Vehicle Dynamics Analysis, Non-Linear (VDANL) simulation, are presented. Specifically, the improvements include changing the simulation's tire dynamics from first-order system tire side force lag dynamics to second-order system tire slip angle dynamics. A second-order system representation is necessary to model underdamped characteristics of tires at high speeds. Lagging slip angle (an input to the tire model) causes all slip angle dependent tire force and moment outputs to be lagged.

There exists a fairly extensive set of tire force measurements performed on dry pavement. But in order to develop a low-coefficient of friction tire model, a set of tire force measurements made on wet pavement is required. Using formulations and parameters obtained on dry roads, and then reducing friction level to that of a wet road is not sufficient to model tire forces in a high fidelity simulation. This paper describes the process of more accurately modeling low coefficient tire forces on the National Advanced Driving Simulator (NADS). It is believed that the tire model improvements will be useful in many types of NADS simulations, including ESC and other advanced vehicle technology studies. In order to produce results that would come from a road surface that would be sufficiently slippery, a set of tires were shaved to 4/32 inches and sent to a tire-testing lab for measurement.

This paper presents results from recent studies on using pulse inputs to generate simulated and experimental frequency responses. The purpose of the paper is to disseminate information on the application of pulse testing methods, and to compare the results with frequency response results obtained using other methods. Frequency responses were generated from a vehicle handling dynamics simulation, from full-scale vehicle handling tests, and from dynamic tire tests. The requirements on the input pulses used to drive the systems under study are discussed, including pulse size, shape, and duration, and the corresponding pulse frequency content and power spectral densities. Pulse testing is generally faster and cheaper than the alternative test methods, and for the case of full-scale vehicle testing, requires much less test area.

This paper presents the application of pulse input techniques to study tire dynamics in the frequency domain. Many tire researchers analyze tire dynamics by means of studying the frequency response of tire output responses to sinusoidal frequency inputs, for example, the frequency response of tire lateral force to sinusoidal slip angle input. To replace expensive and time-consuming sinusoidal frequency tests, pulse techniques are applied to obtain frequency responses. A series of slip angle pulse input tests in various conditions (several normal forces, speeds and magnitudes of slip angle inputs) are executed on a pneumatic tire. The tire output responses to the slip angle pulse inputs are transformed into the frequency domain using discrete Fourier transform. Several rules of Fourier transform related to the study of tire dynamics are detailed. The frequency responses obtained by pulse techniques are validated by comparison with the results from sinusoidal frequency tests.

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).