公开(公告)号：US20250067224A1

公开(公告)日：2025-02-27

申请号：US18454839

申请日：2023-08-24

Applicant: THE BOEING COMPANY

Inventor： Forest Sutton ,  Stephen Solomon Altus ,  Samantha Schwartz ,  Hendrik Schoeniger ,  Michael Christian Büddefeld ,  Maximilian Peter Juengst ,  Salin Maharjan ,  Andrea Sanzone

IPC: F02C9/44 ,  B64D45/00 ,  G08G5/00

Abstract: A system includes one or more control units configured to determine one or more fuel consumption models for an aircraft. A method includes determining, by one or more control units, one or more fuel consumption models for an aircraft. A non-transitory computer-readable storage medium comprising executable instructions that, in response to execution, cause one or more control units comprising a processor, to perform operations including determining one or more fuel consumption models for an aircraft.

公开(公告)号：US12276231B2

公开(公告)日：2025-04-15

申请号：US18454839

申请日：2023-08-24

Applicant: THE BOEING COMPANY

Inventor： Forest Sutton ,  Stephen Solomon Altus ,  Samantha Schwartz ,  Hendrik Schoeniger ,  Michael Christian Büddefeld ,  Maximilian Peter Juengst ,  Salin Maharjan ,  Andrea Sanzone

IPC: F02C9/44 ,  B64D45/00 ,  G08G5/00

Abstract: A system includes one or more control units configured to determine one or more fuel consumption models for an aircraft. A method includes determining, by one or more control units, one or more fuel consumption models for an aircraft. A non-transitory computer-readable storage medium comprising executable instructions that, in response to execution, cause one or more control units comprising a processor, to perform operations including determining one or more fuel consumption models for an aircraft.

公开(公告)号：US20230401456A1

公开(公告)日：2023-12-14

申请号：US17806021

申请日：2022-06-08

Applicant: THE BOEING COMPANY

Inventor： Hendrik Schoeniger ,  Millie Irene Sterling ,  Andrea Sanzone

IPC: G06N5/02

CPC classification number: G06N5/022

Abstract: A method includes receiving a data source that includes information associated with one or more airports. The method also includes determining, using a first machine-learning model, a particular classification of the data source and scheduling information associated with the data source. The method further includes allocating, using a second machine-learning model, particular information in the data source to a particular airport. The particular airport is associated with a particular database, and the particular information is scheduled to be descriptive of a feature of the particular airport. The method also includes generating, using a third machine-learning model, an updated dataset based on the particular information. The current dataset is indicative of the feature of the particular airport. The method further includes updating the current dataset in the particular database with the updated dataset based on the scheduling information in response to a user verification.