The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Oct. 04, 2022
Filed:
Jul. 30, 2019
Bridgestone Europe Nv/sa [be/be], Zaventem, BE;
Vincenzo Ciaravola, Rome, IT;
Marco Andrea Maggi, Rome, IT;
Alfredo Corollaro, Rome, IT;
Lorenzo Alleva, Rome, IT;
Alessandro Boldrini, Rome, IT;
Valerio Bortolotto, Rome, IT;
Rufini Flavia, Rome, IT;
Bridgestone Europe N.V./S.A., Zaventem, BE;
Abstract
The invention concerns a tread wear monitoring method comprising a preliminary step () and a tread wear monitoring step (). The preliminary step () includes: performing tread wear tests on one or more tires; measuring tread-wear-related quantities and first frictional-energy-related quantities, wherein the tread wear-related quantities are indicative of tread wear resulting from the performed tread wear tests, and the first frictional-energy-related quantities are related to frictional energy which the tested tire(s) is/are subject to during the performed tread wear tests; and determining a calibrated tread wear model based on the measured tread-wear-related and first frictional-energy-related quantities. The tread wear monitoring step () includes: acquiring, from a vehicle bus () of a motor vehicle () equipped with two or more wheels fitted, each, with a tire, driving-related quantities related to driving of the motor vehicle (); computing, based on the acquired driving-related quantities and a predefined vehicle dynamics model related to the motor vehicle (), second frictional-energy-related quantities related to frictional energy experienced, during driving, by at least one tire of the motor vehicle (); estimating, based on the second frictional-energy-related quantities and the calibrated tread wear model, tread wear experienced by said at least one tire of the motor vehicle () during driving; and estimating a current average remaining tread material amount of said at least one tire of the motor vehicle () based on the estimated tread wear. Additionally, the preliminary step () further includes: determining, based on one or more of the measured tread-wear-related quantities, a first correction factor related to irregular tread wear due to tire features; and training an artificial neural network to provide second correction factors related to irregular tread wear due to tire usage. Finally, the tread wear monitoring step () further includes: providing a second correction factor by means of the trained artificial neural network based on one or more of the acquired driving-related quantities; and computing a corrected remaining tread material amount based on the current average remaining tread material amount, the first correction factor and the second correction factor provided by the trained artificial neural network based on the one or more acquired driving-related quantities.