Acoustic multi-objective optimization of porous media properties of a diesel particulate filter

Studies on emission control systems have proliferated because of increasing environmental regulations in recent decades. One of the most important emission control systems in vehicles is the Diesel Particulate Filter (DPF). DPFs are important for not only the harmful emission of soot particles but also acoustic emissions. In this study, the acoustic behavior of DPFs was investigated. The study presents an acoustic multi-objective optimization of the porous media properties of a DPF. The multi-objective optimization was performed using the Non-Dominated Sorting Genetic Algorithm (NSGA-II) to obtain an optimum DPF design. In this study, we aimed to maximize the acoustic transmission losses (TL) of the DPF and minimize the pressure drop according to the porous media properties. The DPF wall permeability, channel width, channel wall thickness and channel number were chosen from the porous media properties as design variables for the optimization problem. Test studies have been conducted to validate the mathematical model utilized in optimization. Following these investigations, it has been concluded that the mathematical model, verified through experimental research, is now considered a viable model for resolving the optimization problem. As a result, an optimum DPF design that provides both objective functions was proposed.