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Fatigue life estimation on a parking pawl

ClientEcotuned TechnologiesIndustryTransport & MobilitySoftware3DEXPERIENCEAuthorBenjamin BeckelynckShare

Key results:

1. Identification and understanding of the worst-case static situation
2. Fatigue life estimation and design correction suggestions

Ecotuned Technologies reached out to Optimec to study the parking pawl of their gearbox. Load cases were established by the customer and were reproducing parking situations. The corresponding torque was applied to the gear forcing on the parking pawl with non-linear contact definition.

3.Saving time on physical tests

The study provided Ecotuned Technologies with the opportunity to reduce the number of iterations of physical tests. This study enhances the understanding of the behavior of the material in high cycle fatigue, refines the understanding of the distribution of the stress in the part and the behavior of the mechanical assembly. It allows Ecotuned Technologies to make faster decisions in the early design phase and provides a tool for further iterations. Application of the same torque applied in the physical tests allows Ecotuned Technologies to validate the model.

The two main challenges:

1. Modeling a representative mechanism involving non-linear contact
2. Determining the appropriate material and surface finish for life estimation

The 3DExperience 2022x platform was used to model the mechanism, using CATIA tools to position the gear in contact with the parking pawl in different situations. Meshing and connections were defined involving springs and hinges.

MODSIM enables the use of the same FEM representation to accelerate the model preparation and evaluate different senarios for analysis. Abaqus/Standard 2022 solver was used to evaluate static stress and contact pressure.

Fatigue analysis was set up in the 3DExperience 2022x, with a sequence of non-linear frames used to define the duty cycle. The Fe-safe solver was used for fatigue life estimation. Several surface finish values were evaluated to measure the influence on fatigue life estimation.


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