基于响应曲面法的DPF捕集性能多目标优化

Multi-Objective Optimization of Capture Performance of DPF Based on Response Surface Method

以提高整体捕集性能为目的开展柴油机颗粒捕集器(DPF)结构参数多目标优化设计,利用GT-Power建立DPF捕集模型,通过发动机台架试验验证了仿真模型的可靠性。以最大压降和初始过滤效率为优化目标,以孔隙率、孔直径、壁厚、过滤体长度和直径5个结构参数为优化变量,基于Box-Behnken试验设计方法构建了DPF捕集性能二阶响应面模型,通过三维响应面图对结构参数显著性与交互作用进行仿真分析,采用满意度函数法进行多目标参数优化。结果表明,孔直径对最大压降的影响较小,较小的孔隙率与壁厚、较大的过滤体直径有利于降低DPF最大压降,而适当增大过滤体直径与壁厚可提升DPF初始捕集效率。协同优化后的DPF压降较优化前下降51.34%,优化后的DPF初始过滤效率趋近于100%。

The multi-objective optimization design for the structural parameters of diesel particulate filter(DPF)was carried out to improve the overall capture performance.A DPF trap model was first developed with GT-Power software and was verified by the bench test.The maximum pressure drop and initial filtration efficiency were taken as the target of optimization.The structural parameters such as porosity,pore diameter,wall thickness,filter body length and diameter were used as the variables of optimization.Then a second-order response surface model of DPF capture performance was constructed based on the Box-Behnken experimental design method.The significance and interaction of structural parameters were further analyzed by three-dimensional response surface curves.The multi-objective parameter optimization was finally carried out using the satisfaction function method.The results show that the pore diameter has the less effect on the maximum pressure drop,and the smaller porosity and wall thickness and the larger filter body diameter are beneficial to reduce the maximum pressure drop of DPF.However,appropriately increasing the filter body diameter and wall thickness can improve the initial trapping efficiency of DPF.The pressure drop of DPF decreases by 51.34%and the initial filtration efficiency tends to be close to 100%after optimization.