Tire wear estimation using a hybrid machine learning system and method
US10960712B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 28, 2018 |
| Grant date | Mar 30, 2021 |
| Priority date | — |
| Expiry date | Apr 17, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG07C5/008
- WIPO fieldControl
- WIPO sectorInstruments
Abstract
A tire tread wear system may include one or more vehicle sensors and a processor. The processor may include a control module, a geometrical model, a machine learning model, and a switch. The geometrical model may be configured to collect data from the vehicle sensors to determine a dynamic rolling radius of a tire. The geometrical model may be configured to output a tread wear estimation based on the dynamic rolling radius of the tire. The machine learning model may be configured to collect data from the vehicle sensors. The machine learning model may be configured to output a tread wear estimation based on a correlation of the tread wear estimation output from the geometrical model and one or more data instances with a tire tread state. The switch may be configured to activate the geometrical model, the machine learning model, or a combination thereof.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.