Analysis of the dynamic performances of a piston-crankshaft system considering oil-film forces reconstructed by a neural network

F. M. Meng; Y. Z. Hu; H. Wang; Y. Y. Zhang

doi:10.1243/09544070JAUTO256

Analysis of the dynamic performances of a piston-crankshaft system considering oil-film forces reconstructed by a neural network

F. M. Meng^*
, Y. Z. Hu
, H. Wang
, Y. Y. Zhang

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

11 Scopus citations

Abstract

A dynamic modelling method for the piston-crankshaft system in an internal combustion engine, including two-dimensional oil-film forces of the piston pack, was proposed. In order to obtain the dynamic performance of this system, the dynamic equations for the componenls in the system were presented. Meanwhile, a radial base function neural network technology was employed to reconstruct the two-dimensional oil-film forces, which are then coupled to the presented dynamic equations for the components. The validity of the proposed modelling method for the piston-crankshaft system was demonstrated, and conclusions concerning the dynamic performance of the system were drawn.

Original language	English
Pages (from-to)	171-180
Number of pages	10
Journal	Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering
Volume	221
Issue number	2
DOIs	https://doi.org/10.1243/09544070JAUTO256
State	Published - 2007
Externally published	Yes

Keywords

Dynamic performance
Oil-film forces
Piston-crankshaft system
Radial base function neural network
Reconstruction

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10.1243/09544070JAUTO256

Cite this

@article{6c9bd85be7504ea285ea60f6c5bad7b2,

title = "Analysis of the dynamic performances of a piston-crankshaft system considering oil-film forces reconstructed by a neural network",

abstract = "A dynamic modelling method for the piston-crankshaft system in an internal combustion engine, including two-dimensional oil-film forces of the piston pack, was proposed. In order to obtain the dynamic performance of this system, the dynamic equations for the componenls in the system were presented. Meanwhile, a radial base function neural network technology was employed to reconstruct the two-dimensional oil-film forces, which are then coupled to the presented dynamic equations for the components. The validity of the proposed modelling method for the piston-crankshaft system was demonstrated, and conclusions concerning the dynamic performance of the system were drawn.",

keywords = "Dynamic performance, Oil-film forces, Piston-crankshaft system, Radial base function neural network, Reconstruction",

author = "Meng, \{F. M.\} and Hu, \{Y. Z.\} and H. Wang and Zhang, \{Y. Y.\}",

year = "2007",

doi = "10.1243/09544070JAUTO256",

language = "英语",

volume = "221",

pages = "171--180",

journal = "Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering",

issn = "0954-4070",

publisher = "SAGE Publications Inc.",

number = "2",

}

Analysis of the dynamic performances of a piston-crankshaft system considering oil-film forces reconstructed by a neural network. / Meng, F. M.; Hu, Y. Z.; Wang, H. et al.
In: Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, Vol. 221, No. 2, 2007, p. 171-180.

Research output: Contribution to journal › Article › peer-review

TY - JOUR

T1 - Analysis of the dynamic performances of a piston-crankshaft system considering oil-film forces reconstructed by a neural network

AU - Meng, F. M.

AU - Hu, Y. Z.

AU - Wang, H.

AU - Zhang, Y. Y.

PY - 2007

Y1 - 2007

N2 - A dynamic modelling method for the piston-crankshaft system in an internal combustion engine, including two-dimensional oil-film forces of the piston pack, was proposed. In order to obtain the dynamic performance of this system, the dynamic equations for the componenls in the system were presented. Meanwhile, a radial base function neural network technology was employed to reconstruct the two-dimensional oil-film forces, which are then coupled to the presented dynamic equations for the components. The validity of the proposed modelling method for the piston-crankshaft system was demonstrated, and conclusions concerning the dynamic performance of the system were drawn.

AB - A dynamic modelling method for the piston-crankshaft system in an internal combustion engine, including two-dimensional oil-film forces of the piston pack, was proposed. In order to obtain the dynamic performance of this system, the dynamic equations for the componenls in the system were presented. Meanwhile, a radial base function neural network technology was employed to reconstruct the two-dimensional oil-film forces, which are then coupled to the presented dynamic equations for the components. The validity of the proposed modelling method for the piston-crankshaft system was demonstrated, and conclusions concerning the dynamic performance of the system were drawn.

KW - Dynamic performance

KW - Oil-film forces

KW - Piston-crankshaft system

KW - Radial base function neural network

KW - Reconstruction

UR - https://www.scopus.com/pages/publications/33947597317

U2 - 10.1243/09544070JAUTO256

DO - 10.1243/09544070JAUTO256

M3 - 文章

AN - SCOPUS:33947597317

SN - 0954-4070

VL - 221

SP - 171

EP - 180

JO - Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering

JF - Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering

IS - 2

ER -

Analysis of the dynamic performances of a piston-crankshaft system considering oil-film forces reconstructed by a neural network

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Keywords

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