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RESEARCH PAPERS

Prediction of Mechanical Efficiency of Parallel-Axis Gear Pairs

[+] Author and Article Information
H. Xu

Department of Mechanical Engineering, The Ohio State University, 650 Ackerman Road, Columbus, OH 43202

A. Kahraman1

Department of Mechanical Engineering, The Ohio State University, 650 Ackerman Road, Columbus, OH 43202kahraman.1@osu.edu

N. E. Anderson, D. G. Maddock

Advanced Engineering, General Motors Powertrain, 30240 Oak Creek Drive, Wixom, MI 48393

1

Corresponding author.

J. Mech. Des 129(1), 58-68 (Jun 14, 2006) (11 pages) doi:10.1115/1.2359478 History: Received February 27, 2006; Revised June 14, 2006

A computational model is proposed for the prediction of friction-related mechanical efficiency losses of parallel-axis gear pairs. The model incorporates a gear load distribution model, a friction model, and a mechanical efficiency formulation to predict the instantaneous mechanical efficiency of a gear pair under typical operating, surface, and lubrication conditions. The friction model uses a new friction coefficient formula obtained by using a validated non-Newtonian thermal elastohydrodynamic lubrication (EHL) model in conjunction with a multiple linear regression analysis. The load and friction coefficient distribution predictions are used to compute instantaneous torque/power losses and the mechanical efficiency of a gear pair at any given rotational position. Efficiency measurements from gear pairs having various gear designs and surface treatments are compared to model predictions. Mechanical efficiency predictions are shown to be within 0.1% of the measured values, indicating that the proposed efficiency model is accurate. Results of a parametric study are presented at the end to highlight the influence of key basic gear geometric parameters, tooth modifications, operating conditions, surface finish, and lubricant properties on mechanical efficiency losses.

FIGURES IN THIS ARTICLE
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Copyright © 2007 by American Society of Mechanical Engineers
Topics: Friction , Gears , Stress
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References

Figures

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Figure 1

Flowchart for the efficiency prediction methodology

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Figure 2

Geometry used to calculate curvatures and surface velocities

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Figure 3

Measured coefficient of friction as a function of SR at Ph=1GPa. Circles represent the measured values and the solid line is the fitted curve.

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Figure 4

Comparison of EHL model predictions and the measured data at Ph=1GPa and various Ve values

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Figure 5

Comparison of Eq. 8 with actual EHL analysis results for various parameters; Ve=15m∕s, Ph=2.0GPa, R=0.04m, Toil=100°C, S=0μm, unless specified. Circles represent actual EHL results and solid line is from Eq. 8.

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Figure 6

(a) High-speed gear efficiency test machine and (b) the layout of the test machine (43)

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Figure 7

Typical surface roughness profile measured in the profile direction, S=0.3μm

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Figure 8

Comparison of predicted and measured η¯ values for the 23-tooth and 40-tooth gear sets at 6000rpm and a range of input torque; (a) wide face width gears (26.7mm), and (b) medium face width gears (19.5mm)

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Figure 9

Comparison of predicted and measured η¯ values for the 23-tooth and 40-tooth gear sets at 406Nm and within a range of rotational speed; (a) wide face width gears (26.7mm), and (b) medium face width gears (19.5mm)

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Figure 10

Influence of (a)Lin on η¯ for various Np values for S=0.4μm and Toil=100°C, and (b)S on η¯ for various Toil values for Lin=200Nm and Np=2000rpm

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Figure 11

Influence of (a)βn on η¯ for various ψn values, and (b)ϵβ on η¯ for various ϵα values. S=0.4μm, Lin=200Nm, Np=2000rpm, and Toil=100°C.

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Figure 12

Influence of (a)ξβ on η¯ for various ξα values, and (b)χ on η¯ for various δ values. S=0.4μm, Lin=200Nm, Np=2000rpm, and Toil=100°C.

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