An approach for powertrain gear transmission error prediction using the non-linear finite element method

Abstract

Research has established that gear transmission error (TE) is the predominant source of system excitation and via a complex transfer function produces noise in the powertrain system. Thus, reduction and control of TE will result in improved NVH performance. This paper will introduce an accurate method for estimating TE in powertrain transmission systems through an accurate gear contact analysis. To achieve high geometry accuracy, gear tooth geometry will be mathematically generated by using Python script interfacing with finite element analysis (FEA) software instead of importing from other computer aided design (CAD) packages. Real rolling and sliding contact simulations have been achieved by the latest nonlinear FEA techniques. High-quality meshes for contact surfaces have been obtained by advanced surface-based tie constraint techniques. An effective way to reduce TE is through gear microgeometry modification, i.e. crowning, tip relief, and lead correction. Gear micro-geometry modification will be mathematically achieved through Python script interfaced with finite element models.