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公开(公告)号：US11945265B2
公开(公告)日：2024-04-02
申请号：US17226343
申请日：2021-04-09
发明人： Mansoor Alghooneh , Joseph K. Moore , Christopher J. Mettrick , Gregory P. Kakert , Amir Khajepour , Amin Habibnejad Korayem , Yechen Qin , Ehsan Hashemi
IPC分类号： B60C11/24
CPC分类号： B60C11/246
摘要： A method for determining a tire tread wear estimation of a tire includes receiving, by a controller, a direct tire tread wear measurement, when available, performing an indirect tire tread wear estimation, performing a data fusion of the indirect tire tread wear estimation with the direct tire tread wear measurement when available, estimating a percentage tire life remaining and a mileage to end of tire life, and estimating a refined tire tread wear calibration coefficient for performing future indirect tire tread wear estimations.
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公开(公告)号：US12084064B2
公开(公告)日：2024-09-10
申请号：US17933554
申请日：2022-09-20
发明人： Amir Khajepour , Amin Habibnejad Korayem , Ehsan Hashemi , Qingrong Zhao , SeyedAlireza Kasaiezadeh Mahabadi , Yechen Qin
CPC分类号： B60W40/10 , B60W40/13 , G07C5/085 , B60W2040/1315
摘要： A universal machine learning based system for estimating a vehicle state of a vehicle includes one or more controllers executing instructions to receive a plurality of dynamic variables and corresponding historical data. The controllers execute a sensitivity analysis algorithm to determine a sensitivity level for each dynamic variable and corresponding historical data and select two or more pertinent dynamic variables based on the sensitivity level of each dynamic variable and the corresponding historical data. The controllers standardize the two or more pertinent dynamic variables into a plurality of generic dynamic variables, wherein the plurality of generic dynamic variables are in a standardized format that is applicable to any configuration of vehicle, and estimate the vehicle state based on the plurality of generic dynamic variables by one or more machine learning algorithms.
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公开(公告)号：US20240092371A1
公开(公告)日：2024-03-21
申请号：US17933554
申请日：2022-09-20
发明人： Amir Khajepour , Amin Habibnejad Korayem , Ehsan Hashemi , Qingrong Zhao , SeyedAlireza Kasaiezadeh Mahabadi , Yechen Qin
CPC分类号： B60W40/10 , B60W40/13 , G07C5/085 , B60W2040/1315
摘要： A universal machine learning based system for estimating a vehicle state of a vehicle includes one or more controllers executing instructions to receive a plurality of dynamic variables and corresponding historical data. The controllers execute a sensitivity analysis algorithm to determine a sensitivity level for each dynamic variable and corresponding historical data and select two or more pertinent dynamic variables based on the sensitivity level of each dynamic variable and the corresponding historical data. The controllers standardize the two or more pertinent dynamic variables into a plurality of generic dynamic variables, wherein the plurality of generic dynamic variables are in a standardized format that is applicable to any configuration of vehicle, and estimate the vehicle state based on the plurality of generic dynamic variables by one or more machine learning algorithms.
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公开(公告)号：US20220324266A1
公开(公告)日：2022-10-13
申请号：US17226343
申请日：2021-04-09
发明人： Mansoor Alghooneh , Joseph K. Moore , Christopher J. Mettrick , Gregory P. Kakert , Amir Khajepour , Amin Habibnejad Korayem , Yechen Qin , Ehsan Hashemi
IPC分类号： B60C11/24
摘要： A method for determining a tire tread wear estimation of a tire includes receiving, by a controller, a direct tire tread wear measurement, when available, performing an indirect tire tread wear estimation, performing a data fusion of the indirect tire tread wear estimation with the direct tire tread wear measurement when available, estimating a percentage tire life remaining and a mileage to end of tire life, and estimating a refined tire tread wear calibration coefficient for performing future indirect tire tread wear estimations.
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