公开(公告)号：US20240166192A1

公开(公告)日：2024-05-23

申请号：US18057281

申请日：2022-11-21

Applicant: GM Global Technology Operations LLC

Inventor： Yubiao Zhang ,  Qingrong Zhao ,  Edward Joseph Ecclestone

IPC: B60W30/02 ,  B60W40/06

CPC classification number: B60W30/02 ,  B60W40/06 ,  B60W2520/26 ,  B60W2520/28 ,  B60W2520/30

Abstract: A method of estimating a performance characteristic of a wheel of a vehicle, includes selecting relevant input features based on wheel dynamics and tire behavior, and collecting experimental data for each of the relevant input features at each of a plurality of vehicle operating conditions. The method further includes manually identifying and labeling wheel stability status over time from the experimental data and calculating tractive limit over time from the experimental data. The method also includes training a tractive limit model and training a wheel stability status model. The method further includes receiving a plurality of testing inputs, wherein each of the plurality of testing inputs is received from a sensor on-board the vehicle or from a controller on-board the vehicle and, processing the received testing inputs in a predetermined machine learning process to calculate in one or more data processors a prediction of the performance characteristic.

公开(公告)号：US12246700B2

公开(公告)日：2025-03-11

申请号：US18057281

申请日：2022-11-21

Applicant: GM Global Technology Operations LLC

Inventor： Yubiao Zhang ,  Qingrong Zhao ,  Edward Joseph Ecclestone

IPC: B60W30/02 ,  B60W40/06 ,  G06N20/00

Abstract: A method of estimating a performance characteristic of a wheel of a vehicle, includes selecting relevant input features based on wheel dynamics and tire behavior, and collecting experimental data for each of the relevant input features at each of a plurality of vehicle operating conditions. The method further includes manually identifying and labeling wheel stability status over time from the experimental data and calculating tractive limit over time from the experimental data. The method also includes training a tractive limit model and training a wheel stability status model. The method further includes receiving a plurality of testing inputs, wherein each of the plurality of testing inputs is received from a sensor on-board the vehicle or from a controller on-board the vehicle and, processing the received testing inputs in a predetermined machine learning process to calculate in one or more data processors a prediction of the performance characteristic.