2012
DOI: 10.1016/j.proeng.2012.06.192
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Observer Based Road-Tire Friction Estimation for Slip Control of Braking System

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Cited by 14 publications
(9 citation statements)
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“…subject to umin ≤ u ≤ umax (22) where B ∈ R m×n is a control effectiveness matrix, v ∈ R m are the desired accelerations, n is the number of control effectors, and m is the number of axes to control with n > m. In our case, the vehicle is equipped by an ESP, ARS, and RTV. The problem can be defined as follows:…”
Section: Control Allocationmentioning
confidence: 99%
See 1 more Smart Citation
“…subject to umin ≤ u ≤ umax (22) where B ∈ R m×n is a control effectiveness matrix, v ∈ R m are the desired accelerations, n is the number of control effectors, and m is the number of axes to control with n > m. In our case, the vehicle is equipped by an ESP, ARS, and RTV. The problem can be defined as follows:…”
Section: Control Allocationmentioning
confidence: 99%
“…Not only the control should be reconfigurable but also the reference model should be updated. In [22], a sliding mode observer have been designed depending on Dugoff tire model [23]. This latter shows good precision in the linear zone of tire force.…”
Section: Friction Estimationmentioning
confidence: 99%
“…Nilanjan et al [122] proposed a sliding mode observer along with modified Dugoff model to estimate the longitudinal velocity and friction coefficient; the only measured state was wheel angular velocity. Doumiati et al [86] proposed a real time algorithm to estimate the tire-road lateral forces and side slip angle using two estimation algorithms of extended and unscented Kalman filter, in which the lateral force was modeled using Dugoff model.…”
Section: Dugoff Tire Modelmentioning
confidence: 99%
“…However, when slip is more than 0.3, the braking force may be reduced. The tires are completely locked when slip is 1, and the wheels would slide along the pavement [6][7][8][9][10][11]. The results are shown in Figure 2 [12].…”
Section: Introductionmentioning
confidence: 99%