Abstract
In order to improve the overall performance of diesel particulate filter (DPF) in the soot capture process, a multi-objective optimization model is developed based on the objective functions of maximum pressure drop and initial filtration efficiency. Firstly, the sensitivity analysis of the structural parameters of DPF are performed. Then the response surface model based on Box-Behnken is constructed, and diagnostic analysis and analysis of variance (ANOVA) are carried out for each response. Finally, the non-dominated sorting genetic algorithm-II (NSGA-II) is used to obtain the Pareto optimal solution. The research results show that the sensitivity of filter diameter to maximum pressure drop and initial filtration efficiency is higher than other parameters. The multi-objective optimization results are verified by GT-SUITE software, and the maximum relative errors of maximum pressure drop and initial filtration efficiency between the simulation and optimization results are 1.41% and 3.28%, respectively. Compared with the original performance, the initial filtration efficiency of DPF is improved by 16.42%. The optimized DPF pressure drop decreased by 15% and 36.33% at the beginning and end of the filtration period, respectively.
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