Human in the loop (HIL) simulation has experienced a significant increase in popularity in recent years. In this work, a novel approach to traction control is developed and implemented in a HIL environment, exploiting the significant advantages of framing the problem in a manner that more closely matches how a human expert drives a vehicle. An adaptive gradient ascent algorithm is at the heart of the proposed solution to longitudinal traction control. A real-time implementation of the gradient ascent algorithm is developed using linear operator techniques, even though the tyre–ground interface is highly non-linear. The adaptive traction control algorithm is based on two separate, but related, estimation algorithms that estimate both the instantaneous traction force and a unique predictive traction force model. This adaptive control algorithm, the necessary estimation algorithms and their real-time implementation are described in this work. The results, when implemented as a driver assist application on a 6-DOF motion platform, with a HIL, are also presented. This work demonstrates the utility of a 6-DOF motion platform in developing and verifying vehicle control algorithms with a HIL.
Implementation and verification of adaptive longitudinal traction control
Vehicle System Dynamics ; 51 , 11 ; 1674-1694
2013
21 Seiten
Aufsatz (Zeitschrift)
Englisch
Implementation and verification of adaptive longitudinal traction control
Kraftfahrwesen | 2013
|Implementation and verification of adaptive longitudinal traction control
Taylor & Francis Verlag | 2013
|Fuzzy longitudinal traction control
Tema Archiv | 2005
|TIBKAT | 1995
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