Partial loading and surface wear induced by elastic deformation and machining errors are critical factors causing vibration and noise in planetary gear trains. To mitigate these issues, this paper proposes a multi-objective optimization method for gear tooth modification. Based on a comprehensive analysis of the static and dynamic characteristics of a two-stage planetary gear set, a multi-objective function is established to minimize transmission error, meshing force, unit normal load, and tooth root bending stress. A hybrid optimization strategy, integrating a combined weighting method with a Genetic Algorithm (GA), is employed to determine the optimal micro-geometry parameters. Verification is conducted through static-dynamic simulations and prototype experiments. The results demonstrate that transmission error decreases by 18.91% (from 0.37 to 0.30 μ m) after optimization. The meshing force decreases from 65.9 to 56.6 N (13.85%), the unit normal load decreases from 95.4 to 83.5 N/mm (12.47%), and the tooth root bending stress decreases from 270.3 to 220.8 MPa (18.30%). In addition, the peak vibration acceleration is reduced from 8.12 to 5.77 m/s 2 (28.94%), while the noise sound pressure level decreases from 70.2 to 64.8 dB(A) (7.69%). Optimized micro-geometry effectively ameliorates impact shocks during gear engagement and disengagement, thus enhancing transmission efficiency. This study provides a valuable reference for the low-noise design and vibration control of planetary gear reducers.
Gao et al. (2026) studied this question.