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Article Dans Une Revue Mechanism and Machine Theory Année : 2022

Multi-objective optimization of gear unit design to improve efficiency and transmission error

Résumé

This study aims to implement multi-objective optimization of a gear unit in order to minimize the power loss and the vibrational excitation generated by the meshing, via a multi-scale approach that extends from gear contact to the complete transmission. All these indicators are closely linked to the macro and micro-geometry definition of the gear pair. The optimization is carried out using a genetic algorithm, namely the Non-Dominated Sorting Genetic Algorithm II (NSGA-II). The design variables chosen for the problem are the pressure angle and the helix angle, as macro-geometry characteristics of the gear, and/or the length and the amount of tooth profile modifications, as micro-geometry characteristics of the gear. Constraints are imposed in order to not exceed a maximum bending stress at the tooth root of the gear and to not fall below a minimum total contact ratio. From the results obtained, it is found that the multi-objective optimization with both micro and macro-geometry parameters simultaneously gives different results than those obtained with macro-geometry first and then micro-geometry parameters. In order to study the importance, or not, to take account of the complete gear unit, a comparison is made between the local power loss generated by gear tooth friction and the total power loss in the single stage gear unit in terms of design variables values.
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Dates et versions

hal-03659800 , version 1 (25-05-2023)

Identifiants

Citer

E.B. Younes, C. Changenet, J. Bruyère, Emmanuel Rigaud, J. Perret-Liaudet. Multi-objective optimization of gear unit design to improve efficiency and transmission error. Mechanism and Machine Theory, 2022, 167, pp.104499. ⟨10.1016/j.mechmachtheory.2021.104499⟩. ⟨hal-03659800⟩
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