An integrated optimization method for multi-class parameters and multi-dimensional objectives: Application to an advanced transmission
Current transmission design methodologies often optimize single parameters or physical fields, while conventional heuristic algorithms suffer from premature convergence and lack interpretability. To address these limitations, this paper proposes an integrated optimization design method for planetary gear sets and wet clutches. The approach leverages multi-physics simulations to extract evaluation metrics, constructing a comprehensive evaluation index via radar charts and the Analytic Hierarchy Process (AHP). A neural network-based surrogate model is then employed to predict the global solution space and identify optimal designs efficiently. Applied to an advanced transmission system, this method evaluates feasible candidates through integrated system simulation, 3D modeling, and finite element analysis. Results demonstrate significant improvements, increasing the comprehensive evaluation indices of the planetary gear set and wet clutch by 32.9% and 23.8%, respectively. This study offers a practical reference for efficient multi-parameter, multi-objective optimization of complex transmission components.