{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T16:21:15Z","timestamp":1778084475016,"version":"3.51.4"},"reference-count":36,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2023,4,27]],"date-time":"2023-04-27T00:00:00Z","timestamp":1682553600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/s23094326","type":"journal-article","created":{"date-parts":[[2023,4,28]],"date-time":"2023-04-28T02:02:23Z","timestamp":1682647343000},"page":"4326","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["In-Cylinder Pressure Estimation from Rotational Speed Measurements via Extended Kalman Filter"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6861-1869","authenticated-orcid":false,"given":"Renato","family":"Quartullo","sequence":"first","affiliation":[{"name":"Dipartimento di Ingegneria dell\u2019Informazionee Scienze Matematiche, Universit\u00e0 di Siena, 53100 Siena, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4174-073X","authenticated-orcid":false,"given":"Andrea","family":"Garulli","sequence":"additional","affiliation":[{"name":"Dipartimento di Ingegneria dell\u2019Informazionee Scienze Matematiche, Universit\u00e0 di Siena, 53100 Siena, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9756-7817","authenticated-orcid":false,"given":"Antonio","family":"Giannitrapani","sequence":"additional","affiliation":[{"name":"Dipartimento di Ingegneria dell\u2019Informazionee Scienze Matematiche, Universit\u00e0 di Siena, 53100 Siena, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ryota","family":"Minamino","sequence":"additional","affiliation":[{"name":"Yanmar Holdings Co., Ltd., Osaka-shi 8308311, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Giovanni","family":"Vichi","sequence":"additional","affiliation":[{"name":"Yanmar R&D Europe, 50125 Firenze, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,27]]},"reference":[{"key":"ref_1","unstructured":"Heywood, J.B. 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