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Article Dans Une Revue Mechanism and Machine Theory Année : 2017

NVH robust optimization of gear macro and microgeometries using an efficient tooth contact model

Résumé

This paper presents a methodology for the multi-objective optimization of both gear macro and micro-geometry parameters in order to minimize the Static Transmission Error (STE) and the mesh stiffness fluctuations generated by the meshing process. The optimization is performed using a genetic algorithm which allows testing of a high number of gears. As the repetitive calculation process requires a fast evaluation of the gear excitation sources, a semi-analytical tooth bending model is proposed in order to evaluate gear compliance from a thick Reissner-Mindlin analytical plate model for the evaluation of the tooth strain energy and from a Ritz-Galerkin approximation for the description of the tooth deflection form. For each gear design tested by the algorithm, the robustness of solution to manufacturing errors is evaluated by performing Monte Carlo simulations for a thousand samples of random manufacturing errors. The Probability Density Functions (PDF) describing the RMS values of the mesh stiffness and STE fluctuations of each gear are estimated and their average values are the two objectives minimized by the optimization procedure. Standard deviations and maximum values describing the dispersion of results are also evaluated. Finally, the methodology provides a decision help tool for the designer who intends to choose the best gear design according to the criteria retained. The method is illustrated for a mechanical system equipped with a reverse gear.
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Dates et versions

hal-02068279 , version 1 (15-03-2019)

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Pierre Garambois, Joël Perret-Liaudet, Emmanuel Rigaud. NVH robust optimization of gear macro and microgeometries using an efficient tooth contact model. Mechanism and Machine Theory, 2017, 117, pp.78-95. ⟨10.1016/j.mechmachtheory.2017.07.008⟩. ⟨hal-02068279⟩
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