Anti-lock braking system
About: Anti-lock braking system is a research topic. Over the lifetime, 2514 publications have been published within this topic receiving 21849 citations. The topic is also known as: ABS & anti-lock brakes.
Papers published on a yearly basis
TL;DR: The UOT Electric March II as discussed by the authors is an experimental electric vehicle with four in-wheel motors, which is made for intensive study of advanced motion control of an electric vehicle (EV).
Abstract: The electric vehicle (EV) is the most exciting object to apply "advanced motion control" technique. As an EV is driven by electric motors, it has the following three remarkable advantages: 1) motor torque generation is fast and accurate; 2) motors can be installed in two or four wheels; and 3) motor torque can be known precisely. These advantages enable us to easily realize: 1) high performance antilock braking system and traction control system with minor feedback control at each wheel; 2) chassis motion control like direct yaw control; and 3) estimation of road surface condition. "UOT Electric March II" is our novel experimental EV with four in-wheel motors. This EV is made for intensive study of advanced motion control of an EV.
TL;DR: The sliding observer is found promising while the extended Kalman filter is unsatisfactory due to unpredictable changes in the road conditions, and the nonlinear model of the system is shown locally observable.
Abstract: We describe a nonlinear observer-based design for control of vehicle traction that is important in providing safety and obtaining desired longitudinal vehicle motion. First, a robust sliding mode controller is designed to maintain the wheel slip at any given value. Simulations show that longitudinal traction controller is capable of controlling the vehicle with parameter deviations and disturbances. The direct state feedback is then replaced with nonlinear observers to estimate the vehicle velocity from the output of the system (i.e., wheel velocity). The nonlinear model of the system is shown locally observable. The effects and drawbacks of the extended Kalman filters and sliding observers are shown via simulations. The sliding observer is found promising while the extended Kalman filter is unsatisfactory due to unpredictable changes in the road conditions.
TL;DR: The design criteria, and the decision and rule structure of the control system, are described and the simulation results present the system's performance on various road types and under rapidly changing road conditions.
Abstract: Anti-blocking system (ABS) brake controllers pose unique challenges to the designer: a) For optimal performance, the controller must operate at an unstable equilibrium point, b) Depending on road conditions, the maximum braking torque may vary over a wide range, c) The tire slippage measurement signal, crucial for controller performance, is both highly uncertain and noisy, d) On rough roads, the tire slip ratio varies widely and rapidly due to tire bouncing, and e) The braking system contains transportation delays which limit the control system bandwidth. A digital controller design was chosen which combines a fuzzy logic element and a decision logic network. The controller identifies the current road condition and generates a command braking pressure signal, based on current and past readings of the slip ratio and brake pressure. The controller detects wheel blockage immediately and avoids excessive slipping. The ABS system performance is examined on a quarter vehicle model with nonlinear elastic suspension. The parallelity of the fuzzy logic evaluation process ensures rapid computation of the controller output signal, requiring less time and fewer computation steps than controllers with adaptive identification. The robustness of the braking system is investigated on rough roads and in the presence of large measurement noise. This paper describes design criteria, and the decision and rule structure of the control system. The simulation results present the system's performance on various road types and under rapidly changing road conditions.
TL;DR: A hybrid control system with a recurrent neural network (RNN) observer is developed for antilock braking systems and the on-line parameter adaptation laws are derived based on a Lyapunov function, so the stability of the system can be guaranteed.
Abstract: The antilock braking systems are designed to maximize wheel traction by preventing the wheels from locking during braking, while also maintaining adequate vehicle steerability; however, the performance is often degraded under harsh road conditions. In this paper, a hybrid control system with a recurrent neural network (RNN) observer is developed for antilock braking systems. This hybrid control system is comprised of an ideal controller and a compensation controller. The ideal controller, containing an RNN uncertainty observer, is the principal controller; and the compensation controller is a compensator for the difference between the system uncertainty and the estimated uncertainty. Since for dynamic response the RNN has capabilities superior to the feedforward NN, it is utilized for the uncertainty observer. The Taylor linearization technique is employed to increase the learning ability of the RNN. In addition, the on-line parameter adaptation laws are derived based on a Lyapunov function, so the stability of the system can be guaranteed. Simulations are performed to demonstrate the effectiveness of the proposed NN hybrid control system for antilock braking control under various road conditions.
TL;DR: This paper provides a review of state-of-the-art technology and recent developments in TC and ABSs using the actuation of electric motors, with particular attention paid to the realization of slip estimators, the formalization of torque demand, and the control methods applied.
Abstract: Wheel slip control for ground vehicles with individually controlled electric motors can be realized with strategies that can significantly differ from the conventional antilock braking system (ABS) and traction control (TC) system. This paper provides a review of state-of-the-art technology and recent developments in TC and ABSs using the actuation of electric motors. Particular attention is paid to the realization of slip estimators, the formalization of torque demand, and the control methods applied for the implementation of TC and ABSs. The performed analysis allowed for the differentiation of several most elaborated methods for slip and torque control and defining still imperfectly investigated problems to be covered by the further development of TC and ABSs for full electric vehicles.
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