Multi-objective optimization of parallel hydraulic flushing circuit based on NSGA-II
DOI:
https://doi.org/10.15282/ijame.23.3.2026.14.1050Keywords:
Large-scale hydraulic motor, Parallel flushing circuit, Motor test bench, Hydraulic circuit optimization, Multi-objective optimization, AMESimAbstract
In the parallel flushing circuit for large-scale hydraulic motor testing, increasing flushing flow rate raises total pressure loss and casing pressure differential, while reducing pipeline pressure loss alone increases casing pressure. To solve this strongly conflicting engineering problem, this paper proposes an optimization method combining Maximin Latin Hypercube Sampling, Kriging surrogate model and NSGA-II algorithm. Specifically, five core design variables (pipeline lengths, elbow quantities, and pump flow) are systematically tuned to minimize casing pressure difference, minimize total pressure loss, and maximize flushing flow. The TOPSIS method is further applied to derive optimal solutions under different design preferences. The method was verified via AMESim simulation and leave-one-out cross-validation, achieving 0.8%–10.1% optimization for each target, and provides a valuable engineering reference for multi-objective optimization of similar hydraulic circuits. In conclusion, the proposed multi-objective optimization framework successfully resolves the inherent physical contradiction between casing heat dissipation and mechanical seal safety. It proves that combining MLHS, Kriging surrogate models, and NSGA-II is a highly robust approach for large-scale hydraulic test bench design.
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