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Linear stochastic estimation of the coherent structures in internal combustion engine flow

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journal contribution
posted on 21.12.2018, 14:15 by Daniel ButcherDaniel Butcher, Adrian SpencerAdrian Spencer
A methodology for estimating the in-cylinder flow of an internal combustion engine from a number of point velocity measurements (sensors) is presented. Particle image velocimetry is used to provide reference velocity fields for the linear stochastic estimation technique to investigate the number of point measurements required to provide a representative estimation of the flow field. A systematic iterative approach is taken, with sensor locations randomly generated in each iteration to negate sensor location effects. It was found that an overall velocity distribution accuracy of at least 75% may be achieved with 7 sensors and 95% with 35 sensors, with the potential for fewer if sensor locations are optimised. The accuracy of vortex centre location predictions is typically within 2–3 mm, suggesting that the presented technique could characterise individual cycle flow fields by indicating vortex locations, swirl magnitude or tumble, for example. With this information on the current cycle, a control system may be enabled to activate in-cycle adjustment of injection and/or ignition timing, for example, to minimise emissions.

History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Aeronautical and Automotive Engineering

Published in

International Journal of Engine Research

Volume

21

Issue

9

Pages

1738-1749

Citation

BUTCHER, D.S.A. and SPENCER, A., 2020. Linear stochastic estimation of the coherent structures in internal combustion engine flow. International Journal of Engine Research, 21 (9), pp.1738-1749.

Publisher

SAGE Publications © IMechE

Version

AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

15/12/2018

Publication date

2019-01-21

Copyright date

2019

Notes

This paper was published in the journal International Journal of Engine Research and the definitive published version is available at https://doi.org/10.1177/1468087418824896.

ISSN

1468-0874

eISSN

2041-3149

Language

en