Simulation methodology for the identification of critical operating conditions of planetary journal bearings in wind turbines

Abstract

AbstractThe usage of journal bearings as planetary bearings in wind turbines instead of roller bearings has become more common in recent years. Their usage is advantageous, due to smaller installation space needed compared to roller bearings allowing for higher power densities of wind turbine drive trains. However, this technology presents a challenge since there is currently no standardized approach for the design of planetary journal bearings regarding wear. Due to varying wind speeds and dynamic operating events a large variation of loads has to be considered in the design process of a planetary journal bearing for wind turbines. Some of these loads are considered potentially critical to the journal bearing in terms of wear. Identifying these critical load areas early in the design phase supports a reliable bearing design and wind turbine operation.This paper introduces a method to identify critical operating conditions for planetary journal bearings using a simulation tool chain, which couples a multi body simulation (MBS) model of a wind turbine with an elasto-hydrodynamic (EHD) model of the planetary journal bearing. Based on the EHD results critical operating conditions are determined for the planetary bearing. Furthermore, methods are implemented to reduce the number of required EHD simulations for analysing the bearing design. The combination of the identification of critical operating conditions, while reducing the computational effort leads to a simulation methodology, which enables a faster bearing design assessment considering the wide variation of wind turbine operating conditions. The applicability of this method is demonstrated by a simplified use case.Firstly, this paper introduces the MBS model and the parameter space that describes possible combinations of bearing loads such as forces, moments and rotational speed. Due to the number of combinations and the EHD computing effort, the identified parameter space is secondly sampled statistically to reduce the simulation effort. A risk map is derived from the EHD results, to easily indicate potentially critical operating conditions for the planetary journal bearing.