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Technical Paper

A study of road identification for anti-lock brake systems equipped only with wheel speed sensors

2000-06-12
2000-05-0236
Anti-lock brake systems (ABS) are now widely accepted and used on more and more motor vehicles. With the consideration of low product cost and technologies currently available, standard ABS has only wheel speed sensors to detect wheel angular velocities, not enough to directly obtain wheel slip ratios needed by control unit, but to calculate reference slip ratios with measured wheel angular velocities and estimated vehicle speed. Therefore, the road friction coefficient, which dominates vehicle deceleration during severe braking, is an important parameter in estimating vehicle speed. This paper analyzed wheel acceleration responses in simulations of severe braking on different road surfaces, and selected a pair of specific points to mark the wheel acceleration curve under each certain operating condition, such as road surface, pedal-braking torque and wheel vertical load.
Technical Paper

Design of Two Wheel Steer Vehicle Using Optimal Control Algorithm of Four Wheel Steer

1993-11-01
931914
Nonlinear and linear state equstions of 3 dof vehicle model for steering are derived by a symbolic computation software, MACSYMA. As these state equations are in symbolic form, the vehicle design variables for steering can be derived also in closed form. Then by putting the poles of the linear state equation to those of the optimal closed loop, an improved tunning of the vehicle steering response is obtained for two wheel steering vehicle.
Technical Paper

Neuro Controlled Active Suspension with Preview for Ride Comfort

1993-11-01
931969
The objective of this study is to develop a neuro controlled active suspension for the ride quality improvement. The performance index of the optimal control is represented as the frequency-shaped using Parseval's theorem. The incorporation of frequency-dependent weighting matrices allow one to emphasize the specific variables related to the vibrations of the specific bands of frequencies. Once the active control law is obtained, we use the artificial neural networks to train the neuro controller to learn the relation of road input and control force. From the numerical results, we found that back propagation learning does good pattern matching and the neuro controlled suspension may reduce the vertical acceleration of the driver's seat and sprung mass motions significantly at desired bands of frequencies.
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