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FE-analytical slice model and verification test for load distribution analysis and optimization of planetary gear train in wind turbine

Lookup NU author(s): Professor Zhiqiang Hu

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

© 2024 Elsevier LtdLoad distribution behavior of planetary gear train (PGT) is crucial for the contact and bending fatigue failure of wind turbine transmission system. With the increasing power of wind turbines, the load and failure rate of wind turbine become larger, which leads to the demand of accurate and efficient modeling, analysis and optimization for load distribution of PGT. In this paper, a new efficient and accurate FE-analytical slice model for load distribution analysis and optimization of PGT in wind turbine is proposed, which is explicitly formulated by the geometry slice model of external/internal gear contact, original FE-analytical slice model for local contact deformation, and efficient finite element (FE) model for global structural deformation. In the FE-analytical slice model, geometry errors are effectively descripted by discretizing gears into a series of slices, while gear tooth contact elasticity and structural elasticity are addressed by the FE-analytical method accurately and efficiently. Upon the proposed model, the load distribution behaviors of PGT with coupling effects of elasticity and errors are revealed and optimized by tooth modification and in-phase eccentricity arrangement strategy. The load distribution tests of PGT in wind turbine are conducted, verifying the proposed FE-analytical slice model which is significant to improve the load-bearing capacity and avoid the fatigue failure of wind turbine transmission system.


Publication metadata

Author(s): Zhang C, Hu Y, Hu Z, Liu Z

Publication type: Article

Publication status: Published

Journal: Engineering Failure Analysis

Year: 2024

Volume: 162

Print publication date: 01/08/2024

Online publication date: 17/05/2024

Acceptance date: 14/05/2024

Date deposited: 29/07/2024

ISSN (print): 1350-6307

ISSN (electronic): 1873-1961

Publisher: Elsevier Ltd

URL: https://doi.org/10.1016/j.engfailanal.2024.108451

DOI: 10.1016/j.engfailanal.2024.108451

ePrints DOI: 10.57711/n2tm-xe85

Data Access Statement: Data will be made available on request.


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Funding

Funder referenceFunder name
National Natural Science Foundation of China

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