Authors:
Stephen Saric
and
Alireza Bab-Hadiashar
Affiliation:
Faculty of Engineering and Industrial Sciences, Swinburne University of Technology, Australia
Keyword(s):
Brake-by-wire, sensor fusion, dynamic stiffness, torque balance, optimisation.
Related
Ontology
Subjects/Areas/Topics:
Informatics in Control, Automation and Robotics
;
Nonlinear Signals and Systems
;
Optimization Problems in Signal Processing
;
Real-Time Systems Control
;
Signal Processing, Sensors, Systems Modeling and Control
;
System Identification
Abstract:
Removing a clamp force sensor from brake-by-wire (BBW) system designs has been driven by the need to reduce costs and design complexities. In this paper an improved method is presented to estimate clamp force using other sensory information. The proposed estimator is based on the Kalman filter where the actuator resolver is used in a dynamic stiffness model and the actuator current sensors as well as the resolver are used to give measurement updates in a torque balance model. Experimental results show that the estimator can handle highly dynamic braking scenarios making it suitable for possible use in anti-lock braking system (ABS) controls. A comparison is made with a previous attempt to estimate clamp force in BBW systems and it is shown that the proposed estimator improves the root mean square error (RMSE) of estimation. A training strategy is explained to ensure that the estimator can adequately adapt to parameter variations associated with wear. This paper finally discusses reli
ability issues associated with the developed clamp force estimator.
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