公开(公告)号：US20190145859A1

公开(公告)日：2019-05-16

申请号：US16180703

申请日：2018-11-05

Applicant: Tula Technology, Inc.

Inventor： Shikui Kevin CHEN ,  Aditya MANDAL ,  Li-Chun CHIEN ,  Elliot ORTIZ-SOTO

IPC: G01M15/11 ,  G06N3/08 ,  G06N20/00 ,  G06N5/04 ,  F02D35/02

Abstract: Using machine learning for misfire detection in a Dynamic firing level modulation controlled internal combustion engine is described. A neural network is used to calculate expected crank acceleration from various inputs, including the dynamically defined cylinder skip fire sequence. The output of the neural network is then compared to a signal indicative of the measured crank acceleration. Based the comparison, a prediction is made if a misfire has occurred or not. In alternative embodiment, the neural network is expanded to include the measured crank acceleration as an additional input. With the latter embodiment, the neural network is arranged to directly predict misfire events.