Research on Road Friction Coefficient Estimation Algorithm Based on Extended Kalman Filter

Sun, Zengqi; Zhu, Tianjun; Zheng, Hui

doi:10.1109/icicta.2008.38

Cited by 8 publications

(1 citation statement)

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“…In Acosta Lu´a et al, 10 an adaptive controller for a ABS laboratory estimating the friction coefficient was proposed. The authors Sun et al 11 used an extended Kalman filter to estimate the friction coefficient. In this paper, we develop a solution to this issue in the form of an adaptive controller that tracks the optimal slip ratio and estimates online the road characteristics (using a suitable parameter estimator) based on LuGre tire-road friction model.…”

Section: Introductionmentioning

confidence: 99%

Optimal control for anti-lock braking system: Output feedback adaptive controller design and processor in the loop validation test

El-bakkouri

Ouadi

Giri

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part D:

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In this paper, the problem of controlling anti-lock braking system (ABS) was considered. Based on LuGre friction model, an output-feedback adaptive controller that enjoys good braking performances whatever the road conditions, was developed. Specifically, the controller tracks the optimal slip coefficient and, unlike previous work, the reference slip ratio is online estimated according to road conditions as well as longitudinal vehicle speed. The adaptive feature of the controller proves to be crucial for compensating the uncertainty on the changing road characteristics. The controller consists of: (i) a generator of the reference signal for the slip coefficient designed in the form of a neural network; (ii) a nonlinear observer for estimating the internal friction state; (iii) a backstepping adaptive control law, designed on the basis of a quarter-car model, that ensures tracking of the optimal slip value and providing estimates of the model unknown parameters. The controller stability properties are analyzed using Lyapunov stability tools. The theoretical stability results are confirmed by processor-in-the-loop (PIL) experiments in different road conditions. A comparative study, a robustness test, and a co-simulation involving CarSim and MATLAB/Simulink were made to highlight the much better performances, in terms of stability, tracking, robustness, and practicability of the new controller.

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Section: Introductionmentioning

confidence: 99%