Research Papers: Internal Combustion Engines

Systematic Assessment of Rigid Internal Combustion Engine Dynamic Coupling

[+] Author and Article Information
D. Geoff Rideout1

Department of Mechanical Engineering, S.J. Carew Building,  Memorial University, St. John’s, NL, A1B 3X5, Canadagrideout@engr.mun.ca

Jeffrey L. Stein

Automated Modeling Laboratory, Department of Mechanical Engineering, University of Michigan, G029 Auto Lab, 1231 Beal Avenue, Ann Arbor, MI 48109-2121stein@umich.edu

Loucas S. Louca

Department of Mechanical and Manufacturing Engineering, University of Cyprus, 75 Kallipoleos Street, P.O. Box 20537, 1678 Nicosia, Cypruslslouca@ucy.ac.cy


Corresponding author.

J. Eng. Gas Turbines Power 130(2), 022804 (Feb 29, 2008) (12 pages) doi:10.1115/1.2795770 History: Received June 28, 2006; Revised July 11, 2007; Published February 29, 2008

Accurate estimation of engine vibrations is essential in the design of new engines, engine mounts, and the vehicle frames to which they are attached. Mount force prediction has traditionally been simplified by assuming that the reciprocating dynamics of the engine can be decoupled from the three-dimensional motion of the block. The accuracy of the resulting one-way coupled models decreases as engine imbalance and cylinder-to-cylinder variations increase. Further, the form of the one-way coupled model must be assumed a priori, and there is no mechanism for generating an intermediate-complexity model if the one-way coupled model has insufficient fidelity. In this paper, a new dynamic system model decoupling algorithm is applied to a Detroit Diesel Series 60 in-line six-cylinder engine model to test one-way coupling assumptions and to automate generation of a proper model for mount force prediction. The algorithm, which identifies and removes unnecessary constraint equation terms, is reviewed with the aid of an illustrative example. A fully coupled, balanced rigid body model with no cylinder-to-cylinder variations is then constructed, from which x, y, and z force components at the left-rear, right-rear, and front engine mounts are predicted. The decoupling algorithm is then applied to automatically generate a reduced model in which reciprocating dynamics and gross block motion are decoupled. The amplitudes of the varying components of the force time series are predicted to within 8%, with computation time reduced by 55%. The combustion pressure profile in one cylinder is then changed to represent a misfire that creates imbalance. The decoupled model generated by the algorithm is significantly more robust to imbalance than the traditional one-way coupled models in the literature; however, the vertical component of the front mount force is poorly predicted. Reapplication of the algorithm identifies constraint equation terms that must be reinstated. A new, nondecoupled model is generated that accurately predicts all mount components in the presence of the misfire, with computation time reduced by 39%. The algorithm can be easily reapplied, and a new model generated, whenever engine speed or individual cylinder parameters are changed.

Copyright © 2008 by American Society of Mechanical Engineers
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Figure 4

Conditioned bond graph showing partitions

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Figure 5

Engine schematic

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Figure 16

Conditioned misfire model: front mount forces

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Figure 17

Conditioned misfire model: left-rear mount forces

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Figure 18

Computation time, balanced engine

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Figure 15

Partitioned model: left-rear mount forces with misfire

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Figure 14

Partitioned model: front mount forces with misfire

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Figure 13

Engine speed with misfire

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Figure 10

Driven partition power flow schematic

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Figure 9

Driving partition power flow schematic

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Figure 8

Balanced engine speed

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Figure 7

Crankshaft schematic (4)

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Figure 6

Individual cylinder slider crank

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Figure 3

Activity relations for decoupled system

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Figure 2

Example system bond graph

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Figure 1

Illustrative mechanical system example

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Figure 12

Partitioned model: left-rear mount forces

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Figure 11

Partitioned model: front mount forces



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