公开(公告)号：US11526724B2

公开(公告)日：2022-12-13

申请号：US16546887

申请日：2019-08-21

Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

Inventor： Carmen Pedicini ,  Corrado Possieri ,  Vincenzo Alfieri ,  Giuseppe Conte

IPC: G06N3/04 ,  G06N3/08 ,  G07C5/08 ,  G06F17/16 ,  G05D1/00 ,  G05B13/02

Abstract: Provided is a processor-implemented method and a processor in a vehicle for estimating the value of a quantity for which a physical sensor is not available for measurement. The method includes: receiving a plurality of measured signals representing values of measurable variables; computing, in real-time, time derivatives of the measured signals; and applying a trained feedforward neural network, in real-time, to estimate values for a plurality of unmeasurable variables, the unmeasurable variables being variables that are unmeasurable in real-time, the feedforward neural network having been trained using test data containing time derivatives of values for the measurable variables and values for the unmeasurable variables; wherein the vehicle uses the estimated values for the unmeasurable variables for vehicle operation.

公开(公告)号：US20210056377A1

公开(公告)日：2021-02-25

申请号：US16546887

申请日：2019-08-21

Applicant: GM GLOBAL TECHNOLOGY OPERATIONS LLC

Inventor： Carmen Pedicini ,  Corrado Possieri ,  Vincenzo Alfieri ,  Giuseppe Conte

IPC: G06N3/04 ,  G06N3/08 ,  G07C5/08 ,  G05B13/02 ,  G06F17/16 ,  G05D1/00

Abstract: Provided is a processor-implemented method and a processor in a vehicle for estimating the value of a quantity for which a physical sensor is not available for measurement. The method includes: receiving a plurality of measured signals representing values of measurable variables; computing, in real-time, time derivatives of the measured signals; and applying a trained feedforward neural network, in real-time, to estimate values for a plurality of unmeasurable variables, the unmeasurable variables being variables that are unmeasurable in real-time, the feedforward neural network having been trained using test data containing time derivatives of values for the measurable variables and values for the unmeasurable variables; wherein the vehicle uses the estimated values for the unmeasurable variables for vehicle operation.