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A thorough understanding of vehicle exhaust aftertreatment system performance requires time-resolved emissions measurements that accurately follow driving transients, and that are correctly time-aligned with exhaust temperature and flow measurements. The transient response of conventional gas analyzers is characterized by both a time delay and an attenuation of high-frequency signal components. The distortion that this imposes on transient emissions measurements causes significant errors in instantaneous calculations of aftertreatment system efficiency, and thus in modal mass analysis. This creates difficulties in mathematical modeling of emissions system performance and in optimization of powertrain control strategies, leading to suboptimal aftertreatment system designs. A mathematical method is presented which improves the response time of emissions measurements. This begins with development of a model of gas transport and mixing within the sampling and measurement system.

With an emerging need for gasoline particulate filters (GPFs) to lower particle emissions from gasoline direct injection (GDI) engines, studies are being conducted to optimize GPF designs in order to balance filtration efficiency, backpressure penalty, filter size, cost and other factors. Metal fiber filters could offer additional designs to the GPF portfolio, which is currently dominated by ceramic wall-flow filters. However, knowledge on their performance as GPFs is still limited. In this study, modeling on backpressure and filtration efficiency of fibrous media was carried out to determine the basic design criteria (filtration area, filter thickness and size) for different target efficiencies and backpressures at given gas flow conditions. Filter media with different fiber sizes (8 - 17 μm) and porosities (80% - 95%) were evaluated using modeling to determine the influence of fiber size and porosity.