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公开(公告)号:US20210003088A1
公开(公告)日:2021-01-07
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
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.
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公开(公告)号:US20220010744A1
公开(公告)日:2022-01-13
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
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.
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