A 2D finite element based approach to predict the temperature field in polymer spur gear transmissions. (March 2019)

• Record Type: Journal Article
• Authors: Roda-Casanova, Victor; Sanchez-Marin, Francisco
• Is Part Of: Mechanism and machine theory. Volume 133(2019)
• Page Start: 195
• Page End: 210
• Publication Date: 2019-03
• Subjects: Polymer gears -- Frictional heating -- Finite element analysis; Machine theory -- Periodicals; Machinery -- Periodicals; Machines -- Périodiques; Génie mécanique -- Périodiques; Machine theory; Machinery; Periodicals; 621.81
• DOI: 10.1016/j.mechmachtheory.2018.11.019
• Languages: English
• ISSNs: 0094-114X

Abstract

Highlights: A new approach is proposed to predict the temperature of spur gear transmissions. It is suitable for transmissions with any gear geometry, material or lubrication. The new approach can be applied under steady state and transient thermal conditions. The performance of the approach is illustrated with several numerical examples. The accuracy of the results is proved by comparing them to experimental results. Abstract: This article describes a new numerical approach to determine the temperature field of polymer spur gears during their operation. The approach is based on an uncoupled procedure in which a mechanical problem is solved to determine the amount of heat that is generated by friction during the meshing of the gears, and then this heat is considered as a thermal load to perform a thermal analysis of a finite element model of the transmission. The amount of heat generated by friction is determined from the results of a numerical loaded tooth contact analysis of the transmission, which is based on the finite element method. The generality of the finite element method enables this approach to be applied to any kind of spur gear transmission, regardless of the geometry and the material of the gears and lubrication conditions. The resulting approach is applied to determine the temperature field of a spur gear transmission where polymer and metallic gears are combined, under several different operating conditions. The results obtained from this approach are compared to those obtained from experimental analyses, showing a good degree of similarity between them.