WAVELET-BASED ARTIFICIAL NEURAL NET COMBUSITION SENSING

Patent №

US 6,805,099

Granted

2004-10-19

Filed 2002

Owner

DELPHI TECHNOLOGIES, INC.

Lab

AI components

3

ml · planning · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

10286619

A method and apparatus for real-time measurement of combustion characteristics of each combustion event in each individual cylinder coupled with an ability to control the engine based upon the combustion characteristics are shown. The invention includes using selective sampling techniques and wavelet transforms to extract a critical signal feature from an ionization signal that is generated by an in-cylinder ion sensor, and then feeds that critical signal feature into an artificial neural network to determine a desired combustion characteristic of the combustion event. The desired combustion characteristic of the combustion event includes a location of peak pressure, an air/fuel ratio, or a percentage of mass-fraction burned, among others. The control system of the engine is then operable to control the engine based upon the combustion characteristic.

Machine learningPlanningAI hardwareG01L 23/22F02D 35/021F02B 1/12F02D 41/1405

AI classification

Machine learning1.00
Planning0.93
AI hardware0.91
Natural language0.04
Knowledge representation0.01
Evolutionary computation0.00
Vision0.00
Speech0.00

Ownership

DELPHI TECHNOLOGIES, INC.

assignment · 134770511

Assignors

MALACZYNSKI, GERARD WLADYSLAW, BAKER, MICHAEL EDWARD

On an employer assignment, the assignors are typically the inventors.

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