Evidence map›Paper›PMID 37177532›Full record

ArticleSensors (Basel, Switzerland)2023

In-Cylinder Pressure Estimation from Rotational Speed Measurements via Extended Kalman Filter.

Renato Quartullo, Andrea Garulli, Antonio Giannitrapani, Ryota Minamino, Giovanni Vichi

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Renato QuartulloDipartimento di Ingegneria dell'Informazionee Scienze Matematiche, Università di Siena, 53100 Siena, Italy.ORCID 0000-0001-6861-1869
Andrea GarulliDipartimento di Ingegneria dell'Informazionee Scienze Matematiche, Università di Siena, 53100 Siena, Italy.ORCID 0000-0002-4174-073X
Antonio GiannitrapaniDipartimento di Ingegneria dell'Informazionee Scienze Matematiche, Università di Siena, 53100 Siena, Italy.ORCID 0000-0002-9756-7817
Ryota MinaminoYanmar Holdings Co., Ltd., Osaka-shi 8308311, Japan.
Giovanni VichiYanmar R&D Europe, 50125 Firenze, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

in-cylinder pressure estimationinternal combustion engineKalman filter

Identifiers

PMID37177532
PMCPMC10181517

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.