Back to Search Start Over

Analysis of torque efficiency of External Gear Machines considering gear teeth roughness.

Authors :
Pawar, Ajinkya
Manne, Venkata Harish Babu
Vacca, Andrea
Rigosi, Manuel
Source :
Mechanism & Machine Theory. Sep2024, Vol. 199, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

In this paper, External Gear Machine (EGM) torque losses arising from friction at lubricating interfaces are modeled by considering mixed lubrication conditions. A novel contribution of this paper is to consider mixed elastohydrodynamic lubrication contact conditions along with the effect of gear flank surface roughness to determine the meshing losses, which are also the major contributors towards the EGM torque loss. These hydromechanical loss models are integrated in a multibody, multi-physics simulation tool Multics-HYGESim developed at the authors' research center. Experimental activity is performed on two EGM units using different surface finish for gears. Simulated hydromechanical efficiencies match the experimental trends with average deviation of 2.5%. Most importantly, the results capture effects of different gear flank roughness on the torque efficiency. An average increase of 0.9% in the efficiency value is predicted by the simulation model for the EGM with lower teeth roughness, as compared to 1.1% rise obtained via experiments. The proposed torque loss evaluation methodology shows high potential in assisting designers and manufacturers of EGMs to choose the suitable surface finishing for achieving desired hydromechanical performance. • Torque efficiency of external gear machines has been determined via simulation. • Mixed Elasto hydrodynamic lubrication model is used to evaluate meshing frictional loss. • Experimental tests show rise in torque efficiency for lower gear surface roughness. • Computational analysis of lubricating interfaces predicts leakage and friction loss. • Proposed model exhibits potential for virtual prototyping of new gear pump designs. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0094114X
Volume :
199
Database :
Academic Search Index
Journal :
Mechanism & Machine Theory
Publication Type :
Academic Journal
Accession number :
177754940
Full Text :
https://doi.org/10.1016/j.mechmachtheory.2024.105675