Abstract
It is well recognized in the automotive research community that knowledge of the real-time tyre-road friction conditions can be extremely valuable for intelligent safety applications, including design of braking, traction, and stability control systems. This paper presents a new development of an on-line tyre-road adherence estimation methodology and its implementation using both Burckhardt and LuGre tyre-road friction models. The proposed strategy first employs the recursive least squares to identify the linear parameterization (LP) form of Burckhardt model. The identified parameters provide through a Takagi-Sugeno (T-S) fuzzy system the initial values for the LuGre model. Then, it is presented a new large-scale optimization based estimation algorithm using the steady state solution of the partial differential equation (PDE) form of LuGre to obtain its parameters. Finally, real-time simulations in various conditions are provided to demonstrate the efficacy of the algorithm.
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Appendix
Appendix
Vehicle nominal parameters are listed below [6, 10].
\(R_w\): Radius of the wheel = 0.3 [m] | \(J_w\): Rotation inertia of the wheel = 1 [kg.m\(^2\)] |
\(l_f\): Distance from CG to front axles = 1.3 [m] | \(l_r\): Distance from CG to rear axles = 1.4 [m] |
\(d_f,d_r\): Distances between front/rear wheels = 0.9 [m] | h: Height of CG = 0.5 [m] |
\(M_v\): Mass of the vehicle at CG = 900 [kg] | L: Road/tyre patch length = 0.2 [m] |
\(\omega _{rot}\): Model parameter of EMB dynamic = 70 [rad/s] | \(\mu _c\): Normalized coulomb friction = 0.8 |
\(\sigma _0 \): Rubber longitudinal lumped stiffness = 181.54 [1/m] | \(\mu _s\): Normalized static friction = 1.55 [m] |
\(\sigma _1 \): Rubber longitudinal lumped damping = 4.94 [s/m] | \(\sigma _2 \): Viscous relative damping = 0.0018 [s/m] |
\(\tau _M \): Delay parameter of EMB dynamic = 10 [ms] | \(v_0 \): Stribeck relative velocity = 6.57 [m/s] |
\(c_1\): Maximum value of friction curve = [0.19, 1.28] | \(c_3\): \(\mu (\lambda _{opt})-\mu (1)\) = [6.46, 94.13] |
\(c_2\): Maximum value of friction curve shape = [0.06, 0.67] |  |
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Sharifzadeh, M., Timpone, F., Farnam, A., Senatore, A., Akbari, A. (2017). Tyre-Road Adherence Conditions Estimation for Intelligent Vehicle Safety Applications. In: Boschetti, G., Gasparetto, A. (eds) Advances in Italian Mechanism Science. Mechanisms and Machine Science, vol 47. Springer, Cham. https://doi.org/10.1007/978-3-319-48375-7_42
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DOI: https://doi.org/10.1007/978-3-319-48375-7_42
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