公开(公告)号：US11326534B2

公开(公告)日：2022-05-10

申请号：US17407984

申请日：2021-08-20

Applicant: Tula Technology, Inc.

Inventor： Shikui Kevin Chen ,  Aditya Mandal ,  Li-Chun Chien ,  Elliott Ortiz-Soto

IPC: F02D41/14 ,  F01N13/10 ,  F02D41/00 ,  F02D41/22 ,  F02B5/02 ,  F02B9/04 ,  G06N20/00 ,  G06N5/04

Abstract: Using machine learning for cylinder misfire detection in a dynamic firing level modulation controlled internal combustion engine is described. In a classification embodiment, cylinder misfires are differentiated from intentional skips based on a measured exhaust manifold pressure. In a regressive model embodiment, the measured exhaust manifold pressure is compared to a predicted exhaust manifold pressure generated by neural network in response to one or more inputs indicative of the operation of the vehicle. Based on the comparison, a prediction is made if a misfire has occurred or not. In yet other alternative embodiment, angular crank acceleration is used as well for misfire detection.

公开(公告)号：US11125175B2

公开(公告)日：2021-09-21

申请号：US17026706

申请日：2020-09-21

Applicant: Tula Technology, Inc.

Inventor： Shikui Kevin Chen ,  Aditya Mandal ,  Li-Chun Chien ,  Elliott Ortiz-Soto

IPC: F02D41/14 ,  F02B5/02 ,  F01N13/10 ,  F02D41/00 ,  F02D41/22 ,  F02B9/04 ,  G06N20/00 ,  G06N5/04

Abstract: Using machine learning for cylinder misfire detection in a dynamic firing level modulation controlled internal combustion engine is described. In a classification embodiment, cylinder misfires are differentiated from intentional skips based on a measured exhaust manifold pressure. In a regressive model embodiment, the measured exhaust manifold pressure is compared to a predicted exhaust manifold pressure generated by neural network in response to one or more inputs indicative of the operation of the vehicle. Based on the comparison, a prediction is made if a misfire has occurred or not. In yet other alternative embodiment, angular crank acceleration is used as well for misfire detection.

公开(公告)号：US10816438B2

公开(公告)日：2020-10-27

申请号：US16180703

申请日：2018-11-05

Applicant: Tula Technology, Inc.

Inventor： Shikui Kevin Chen ,  Aditya Mandal ,  Li-Chun Chien ,  Elliott Ortiz-Soto

IPC: G01M15/11 ,  F02D35/02 ,  G06N3/08 ,  G06N5/04 ,  G06N20/00 ,  F02D41/00 ,  F02D41/14 ,  G06N3/04

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.