Improving the uncertainty of measured and calculated data in engine problems using the equalisation calculus

A selected example of the application of the equalization calculus to reconcile the results of experimental tests of a spark-ignition internal combustion engine is presented. The example concerns the selection of characteristic parameters of the theoretical Seiliger-Sabathe cycle in accordance with the experimentally determined real cycle. This is therefore a so-called inverse problem. The isochoric and isobaric loading parameters and the heat distribution number were reconciled. In addition, the effect of applying the reconciliation algorithm twice on the correction of measurement results with gross errors is presented.

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Publication Details

Journal
Silniki Spalinowe/Combustion Engines
Published
2025-09-26
DOI
https://doi.org/10.19206/ce-210987
Primary Topic
Control Systems and Identification
Type
article
Field-Weighted Citation Impact
0.00

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article

Improving the uncertainty of measured and calculated data in engine problems using the equalisation calculus

Z. Żmudka
Silniki Spalinowe/Combustion Engines
Control Systems and Identification
article

Improving the uncertainty of measured and calculated data in engine problems using the equalisation calculus

Z. Żmudka
article en

Abstract

A selected example of the application of the equalization calculus to reconcile the results of experimental tests of a spark-ignition internal combustion engine is presented. The example concerns the selection of characteristic parameters of the theoretical Seiliger-Sabathe cycle in accordance with the experimentally determined real cycle. This is therefore a so-called inverse problem. The isochoric and isobaric loading parameters and the heat distribution number were reconciled. In addition, the effect of applying the reconciliation algorithm twice on the correction of measurement results with gross errors is presented.

Silniki Spalinowe/Combustion EnginesVol. 204(1)
Silesian University of Technology
Openalex Percentile: Top 67%
Control Systems and Identification
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