Work

Optimization of a Wind Turbine Gearbox Design Reducing Component Damage Risk Considering Different Electrical Faults

Year: 2026
Type: article
Abstract: Wind turbine (WT) drivetrains are exposed to high dynamic loads, especially caused by grid and converter faults. Those loads increase the frictional energy in the contact zone of the gearbox bearings and gear wheels and, thus, theoretically, the probability of failure of the gearbox before the WTs reach their service lifetime. To increase the robustness against grid and converter faults, gearboxes can be designed to include these as special load cases. The critical parts of gearboxes regarding the influence of grid and converter faults are the components of the fast-rotating gearbox side. This paper introduces an optimization procedure for the high-speed shaft (HSS) components of a WT gearbox, considering several electrical faults as special load cases. The basis for data collection in this work is a validated multi-body simulation (MBS) model of a WT drivetrain. Initially, a test plan is formulated using Latin hypercube sampling (LHS). Based on the simulation results generated with the detailed MBS model according to the defined test plan, computationally efficient surrogate models are derived that link the design parameters with the objectives of the optimization. The surrogate models are employed to optimize the microgeometry of the gearbox. The process is done for several electrical faults. With the optimization, the risk of damage to the gear wheels can be reduced by 28% with a reduced or equal risk of damage to the HSS bearing, depending on the load case. It is also shown via comparison that the optimal design for one critical fault simultaneously leads to a sufficient improvement for other electrical faults (max. 4% reduction in improvement of objectives). Thus, it is sufficient to do the optimization regarding electrical faults only for one critical fault, reducing the necessary computational effort significantly.
Source: Energies
Language: English
Open Access status: gold
Estimated APC paid: $3,137
OpenAlex ID: W7157341415
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Cites: 3
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