The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Sep. 17, 2024

Filed:

Sep. 10, 2021
Applicant:

Robert Bosch Gmbh, Stuttgart, DE;

Inventors:

Andreas Hopf, Stuttgart, DE;

Erik Tonner, Mehring, DE;

Frank Kowol, Knittlingen, DE;

Jens-Holger Barth, Fellbach, DE;

Konrad Groh, Stuttgart, DE;

Matthias Woehrle, Bietigheim-Bissingen, DE;

Mona Meister, Renningen, DE;

Roland Norden, Kornwestheim, DE;

Assignee:

ROBERT BOSCH GMBH, Stuttgart, DE;

Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
F02D 41/14 (2006.01); G05B 13/02 (2006.01); G06N 3/09 (2023.01);
U.S. Cl.
CPC ...
F02D 41/1405 (2013.01); G05B 13/0265 (2013.01); G06N 3/09 (2023.01); F02D 2041/1433 (2013.01); F02D 2200/0602 (2013.01); F02D 2200/0618 (2013.01);
Abstract

A method for training a data-based evaluation model to determine an opening or closing time of an injection valve based on a sensor signal. The method includes: measuring an operation of the injection valve in order to determine at least one sensor signal and an associated opening or closing time; sampling the sensor signal at a sampling rate in order to obtain a sensor signal time series with sensor signal values; determining a plurality of training data sets by assigning a plurality of evaluation point time series generated from a sensor signal time series to the opening or closing time associated with the sensor signal, wherein the evaluation point time series has a lower temporal resolution than the sensor signal time series; training the data-based evaluation model depending on the determined training data sets.


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