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Tire Wear Estimation Using Hybrid Machine Learning Systems and Methods

A machine learning model, tire technology, applied in machine learning, kernel methods, tire measurement, etc., can solve the problems of increasing complexity and cost, not providing reliable results for tire tread estimation, etc.

Active Publication Date: 2021-11-09
NISSAN MOTOR CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Use of additional sensors adds complexity and cost while generally providing better accuracy
The use of commercially available sensors generally does not provide reliable results for tire tread estimation

Method used

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  • Tire Wear Estimation Using Hybrid Machine Learning Systems and Methods
  • Tire Wear Estimation Using Hybrid Machine Learning Systems and Methods
  • Tire Wear Estimation Using Hybrid Machine Learning Systems and Methods

Examples

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Embodiment Construction

[0030] A vehicle may include one or more sensors for generating or capturing sensor data, such as data corresponding to the vehicle's operating environment, or a portion thereof, or the like. For example, sensor data may include information corresponding to one or more external objects such as pedestrians, remote vehicles, other objects within the vehicle's operating environment, vehicle transportation network geometry, combinations thereof, and the like.

[0031] As used herein, the term "computer" or "computing device" includes any unit or combination of units capable of performing any method disclosed herein, or any part thereof.

[0032] As used herein, the term "processor" refers to one or more processors, such as one or more special purpose processors, one or more digital signal processors, one or more microprocessors, one or more control one or more microprocessors, one or more application processors, one or more application specific integrated circuits, one or more app...

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PUM

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Abstract

The tire tread wear system may include one or more vehicle sensors and a processor. The processor may include control modules, geometric models, machine learning models, and switches. The geometric model may be configured to collect data from vehicle sensors to determine the dynamic rolling radius of the tire. The geometric model may be configured to output a tread wear estimate based on the dynamic rolling radius of the tire. The machine learning model can be configured to collect data from vehicle sensors. The machine learning model may be configured to output a tread wear estimate based on the tread wear estimate output from the geometric model and a correlation with one or more data instances of the tire tread condition. Switches can be configured to activate geometric models, machine learning models, or a combination thereof.

Description

[0001] Cross References to Related Applications [0002] This application claims priority to and benefit of US Application Patent Serial No. 16 / 022,032 filed June 28, 2018, which is hereby incorporated by reference in its entirety. technical field [0003] The present invention relates to vehicle operations management. Background technique [0004] Typical methods used for tire tread estimation can be classified into two groups. The first group uses additional sensors not present in current production vehicles, while the second uses commercially available sensors. The use of additional sensors adds complexity and cost while generally providing better accuracy. The use of commercially available sensors generally does not provide reliable results for tire tread estimation. Ultimately, it would likely be desirable to have an accurate and cost effective system to determine tire tread wear without the need for additional sensors. Contents of the invention [0005] Aspects, ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): B60C23/04B60Q1/00G01M17/02G08B13/14
CPCB60C11/246G07C5/0825G07C5/008G06N20/10B60W40/12G07C5/0808G06N20/00
Inventor G·L·斯托蒂M·瓦科努亨G·D·迪布
Owner NISSAN MOTOR CO LTD