2022
DOI: 10.1016/j.simpat.2021.102484
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A Neural Network Approach for Roughness-Dependent Update of Tyre Friction

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Cited by 9 publications
(2 citation statements)
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“…Moreover, Farroni [17] developed the Tire/Road Interaction Characterization and Knowledge (TRICK) tool, which permits tuning the various models using the vehicle as a lab. Furlan et al [18] provided an artificial neural network model to predict the friction coefficient, including a heat transfer model to calculate the tyre bulk temperature. Mavros [19] proposed a thermo-mechanical model based on an extensive study of the local flash temperature.…”
Section: Introductionmentioning
confidence: 99%
“…Moreover, Farroni [17] developed the Tire/Road Interaction Characterization and Knowledge (TRICK) tool, which permits tuning the various models using the vehicle as a lab. Furlan et al [18] provided an artificial neural network model to predict the friction coefficient, including a heat transfer model to calculate the tyre bulk temperature. Mavros [19] proposed a thermo-mechanical model based on an extensive study of the local flash temperature.…”
Section: Introductionmentioning
confidence: 99%
“…It is well known that the main tractions of a vehicle's forces are transmitted through wheels. Furlan et al [23] presented an implementation of ANNs to predict viscoelastic behavior and the relationship between vehicle speed and road friction. The improvement of powertrains requires standard assistant systems such as cruise control and throttle control enhancing loop control to reduce emission; this problem was solved using ANNs [24,25].…”
Section: Introductionmentioning
confidence: 99%