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动力总成悬置系统悬置参数的优化可以通过移频、解耦、降低支撑处响应力等多种途径来进行,因此,悬置参数的设计是一个多目标优化问题。运用灰色理论中的关联分析的方法,选取粒子群算法中的全局极值和个体极值,并结合稳健设计思想,提出了适合于多目标模型的灰色粒子群稳健优化算法,并将该算法应用到动力总成悬置系统的优化设计中。计算结果表明,该算法不仅能够很好地协调从不同角度提出的悬置参数的优化目标,获得满意的综合效果,而且可以使优化后的悬置参数有更好的鲁棒性。
The optimization of powertrain mounting system suspension parameters can be carried out by frequency shifting, decoupling, reducing the response force of the support and so on. Therefore, the design of suspension parameters is a multi-objective optimization problem. By using the gray relational analysis method, we select the global extremum and the extremum extremum in the particle swarm optimization algorithm, combined with the robust design idea, put forward a gray particle swarm optimization algorithm that is suitable for multi-objective model and apply the algorithm To the powertrain mounting system optimization design. The calculation results show that the proposed algorithm can not only coordinate the optimization objectives of suspension parameters proposed from different angles well, but also achieve satisfactory overall results, and make the optimized suspension parameters more robust.