In-Cylinder Pressure Estimation from Rotational Speed Measurements via Extended Kalman Filter
Real-time estimation of the in-cylinder pressure of combustion engines is crucial to detect failures and improve the performance of the engine control system. A new estimation scheme is proposed based on the Extended Kalman Filter, which exploits measurements of the engine rotational speed provided...
Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
MDPI
2023
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Subjects: | |
Online Access: | View Fulltext in Publisher View in Scopus |
LEADER | 02317nam a2200385Ia 4500 | ||
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001 | 10.3390-s23094326 | ||
008 | 230529s2023 CNT 000 0 und d | ||
020 | |a 14248220 (ISSN) | ||
245 | 1 | 0 | |a In-Cylinder Pressure Estimation from Rotational Speed Measurements via Extended Kalman Filter |
260 | 0 | |b MDPI |c 2023 | |
856 | |z View Fulltext in Publisher |u https://doi.org/10.3390/s23094326 | ||
856 | |z View in Scopus |u https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159236131&doi=10.3390%2fs23094326&partnerID=40&md5=b7c99ca64df6ac99b2f319e365c5e6ac | ||
520 | 3 | |a Real-time estimation of the in-cylinder pressure of combustion engines is crucial to detect failures and improve the performance of the engine control system. A new estimation scheme is proposed based on the Extended Kalman Filter, which exploits measurements of the engine rotational speed provided by a standard phonic wheel sensor. The main novelty lies in a parameterization of the combustion pressure, which is generated by averaging experimental data collected in different operating points. The proposed approach is validated on real data from a turbocharged compression ignition engine, including both nominal and off-nominal working conditions. The experimental results show that the proposed technique accurately reconstructs the pressure profile, featuring a fit performance index exceeding 90% most of the time. Moreover, it can track changes in the engine operating conditions as well as detect the presence of cylinder-to-cylinder variations. © 2023 by the authors. | |
650 | 0 | 4 | |a Combustion |
650 | 0 | 4 | |a Combustion engines |
650 | 0 | 4 | |a Engine control system |
650 | 0 | 4 | |a Engine cylinders |
650 | 0 | 4 | |a Estimation schemes |
650 | 0 | 4 | |a Extended Kalman filters |
650 | 0 | 4 | |a in-cylinder pressure estimation |
650 | 0 | 4 | |a In-cylinder pressure estimation |
650 | 0 | 4 | |a In-cylinder pressures |
650 | 0 | 4 | |a internal combustion engine |
650 | 0 | 4 | |a Kalman filter |
650 | 0 | 4 | |a Performance |
650 | 0 | 4 | |a Pressure estimation |
650 | 0 | 4 | |a Real-time estimation |
650 | 0 | 4 | |a Rotational speed |
650 | 0 | 4 | |a Speed measurement |
700 | 1 | 0 | |a Garulli, A. |e author |
700 | 1 | 0 | |a Giannitrapani, A. |e author |
700 | 1 | 0 | |a Minamino, R. |e author |
700 | 1 | 0 | |a Quartullo, R. |e author |
700 | 1 | 0 | |a Vichi, G. |e author |
773 | |t Sensors |