Realtime Estimation of Adhesion Characteristic between Tyres and Road

Kiencke, Uwe

doi:10.1016/s1474-6670(17)48673-3

Cited by 46 publications

(32 citation statements)

References 1 publication

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“…In this paper this model is approximated by (8) where , , , , and are parameters to be determined. It should be noted that this parameterization is different from all previous parameterizations, including that presented in [9]. As shown in Section VI, (8) accurately approximates the behavior of (7), particularly in the region , where is the point where the maximum coefficient of friction is attained.…”

Section: Tire/road Friction Characteristicsmentioning

confidence: 78%

“…The final map expresses as a function of , the vehicle velocity, , and the normal load on the tire, . Reference [9] presents a procedure for real-time estimation of . A simplification to the analytical model by [7] is introduced in such a way that the relation between and is linear in the parameters.…”

Section: Tire/road Friction Characteristicsmentioning

confidence: 99%

“…A simplification to the analytical model by [7] is introduced in such a way that the relation between and is linear in the parameters. Kiencke [9] used a two stages identification algorithm. In the first stage, the value of is estimated.…”

Section: Tire/road Friction Characteristicsmentioning

confidence: 99%

“…The work in [9]- [11] does not consider any velocity dependence in the derivation of , as suggested by [7] and [8]. An attempt to consider the velocity dependence for antilock braking system (ABS) control is presented in [13].…”

Section: Tire/road Friction Characteristicsmentioning

confidence: 99%

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Adaptive emergency braking control with underestimation of friction coefficient

Alvarez

Horowitz

2002

IEEE Trans. Contr. Syst. Technol.

112

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Abstract-In this paper, a control scheme for emergency braking maneuvers in automated highway systems (AHSs) and a new online identification scheme to determine the tire-road friction characteristics of the vehicle are presented. The proposed controller determines the required pressure in the master cylinder of the braking system to achieve maximum deceleration during braking, based on the estimation of the tire-road friction characteristics and the overall braking system gain, for the given set of parameter estimates. With persistence of excitation, the identified static map between the tire longitudinal slip and the tire-road friction coefficient is guaranteed to converge to the actual map. When there is no persistence of excitation, and under a proper choice of initial conditions and adaptation gains, the proposed scheme underestimates the maximum coefficient of friction and its corresponding slip, and allows a conservative calculation of the safety critical intervehicle spacing.

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Section: Tire/road Friction Characteristicsmentioning

confidence: 78%

Section: Tire/road Friction Characteristicsmentioning

confidence: 99%

Section: Tire/road Friction Characteristicsmentioning

confidence: 99%

Section: Tire/road Friction Characteristicsmentioning

confidence: 99%

See 2 more Smart Citations

Adaptive emergency braking control with underestimation of friction coefficient

Alvarez

Horowitz

2002

IEEE Trans. Contr. Syst. Technol.

112

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show abstract

“…Non-linear parameterizations, such as the Magic Tire Formula [3] or the Burckhardt model [4] should be avoided because of the difficulty in identifying non-linear models in real-time. Therefore, linear parameterizations, like polynomials [5], [6] or fixed exponentials [7] should be privileged for real-time implementations. Motivated by the good approximation properties offered by Neural Networks (NN) [8], in this article we explore the possibility of approximate the friction coefficient function (.)…”

Section: Introductionmentioning

confidence: 99%

A new linear parametrization for peak friction coefficient estimation in real time

Castro

Araújo

Cardoso

et al. 2010

2010 IEEE Vehicle Power and Propulsion Conference

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Abstract-The correct estimation of the friction coefficient in automotive applications is of paramount importance in the design of effective vehicle safety systems. In this article a new parametrization for estimating the peak friction coefficient, in the tire-road interface, is presented. The proposed parametrization is based on a feedforward neural network (FFNN), trained by the Extreme Learning Machine (ELM) method. Unlike traditional learning techniques for FFNN, typically based on backpropagation and inappropriate for real time implementation, the ELM provides a learning process based on random assignment in the weights between input and the hidden layer. With this approach, the network training becomes much faster, and the unknown parameters can be identified through simple and robust regression methods, such as the Recursive Least Squares. Simulation results, obtained with the CarSim program, demonstrate a good performance of the proposed parametrization; compared with previous methods described in the literature, the proposed method reduces the estimation errors using a model with a lower number of parameters.

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Adaptive control approach to uncertain longitudinal tire slip in traction control of vehicles

Nakakuki¹,

Shen²,

Tamura³

2008

Asian Journal of Control

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This paper addresses the longitudinal traction control problem of vehicles. A nonlinear control law at the torque level is shown to cope with the unknown tyre reaction force. From a physical consideration of a vehicle, a decoupling controller design is considered, which enables us to make the controller design straightforward. A parameter estimator is introduced to adaptive control of the system with uncertain frictional coefficient. The proposed controller indicates the better control performance than that of a non-adaptive or a conventional PI controller as evaluated in numerical simulation.

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Realtime Estimation of Adhesion Characteristic between Tyres and Road

Cited by 46 publications

References 1 publication

Adaptive emergency braking control with underestimation of friction coefficient

Adaptive emergency braking control with underestimation of friction coefficient

A new linear parametrization for peak friction coefficient estimation in real time

Adaptive control approach to uncertain longitudinal tire slip in traction control of vehicles

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