A novel sub-objective progressive trade-off optimization method and application in the preliminary design of opposed-piston two-stroke diesel generator sets

The preliminary design of complex systems involves multiple tightly coupled sub-objectives and subsystems, which complicates coordination for achieving a comprehensive optimum. Classical methods like the Multi-Disciplinary Feasible (MDF) and Individual Discipline Feasible (IDF) directly optimize the system-level problem but often encounter multiple local optima. Avoiding local optima requires extensive global exploration, which inevitably increases computational time. To enhance optimization accuracy while reducing computational time, a novel Sub-Objective Progressive Trade-off (OPT) optimization method is proposed and applied to optimize the power generation fuel consumption rate of an opposed-piston two-stroke diesel generator set. It decomposes the system-level optimization into three stages, where three sub-objectives—indicated thermal efficiency, mechanical efficiency, and power generation efficiency—are progressively incorporated into the trade-off process. Local optima caused by single sub-objective’s optimality can be avoided sequentially. The results show that compared to the MDF method with a simulation model, the OPT method reduces the optimal fuel consumption rate by 0.34 g/kWh and cuts the computational time by 67%, and it exhibits a similar improvement in optimization performance compared with the MDF method using a surrogate model. Relative to the IDF method, the OPT method also achieves reductions in the optimal fuel consumption rate and computational time by 1.79 g/kWh and 47.5%, respectively. Moreover, regardless of initial solution differences, all three efficiencies for each optimal solution of the OPT method remain nearly consistent, verifying the avoidance of local optima caused by a single relatively high efficiency. This study presents an efficient optimization method for the preliminary design of complex systems.