Gasoline Particulate Filters (GPF) are widely employed in exhaust aftertreatment systems of gasoline engines to meet the stringent particulate emissions requirements of Euro6 and China6 standard. While providing an effective filtration of particles, the GPF increases the engine backpressure as a penalty due to accumulation of soot. To clean the accumulated soot, periodical burning of soot is achieved by the onboard control models and lot of effort is spent on calibrating the same. In order to understand pressure drop behavior across GPF, detailed pressure drop measurements were conducted at clean, soot and ash loaded conditions at engine dynamometer and at vehicle conditions. Effect of degreening of GPF was studied to take into account any change in pressure drop characteristics of onboard control models during GPF aging in the vehicle.
Then using the collected test data, a pressure drop model is built in GT-Power [1] as a physics based GPF back pressure predictive tool, that can help in reducing the hardware testing. The model parameters are fit for clean, soot, and ash loaded GPF conditions. Initially, clean filter brick parameters like wall permeability and Forchheimer constant are fitted using dynamometer conditions and then applied to vehicle conditions. To fit soot parameters like soot permeability and soot density, pressure drop data under dynamometer conditions with different soot loads are used. The parameters are calibrated for average soot loads and validated for low and high soot conditions. Soot density is specified as a function of soot load and flow rate to consider the effect of soot compression. Effect of break-in or filter aging is included in the model for accurate pressure drop prediction under real driving conditions. The pressure drop predictions under various soot loaded conditions are found to be in good agreement with test data obtained from vehicle conditions. Finally, the model parameters are fitted for ash loaded conditions. Ash parameters like permeability, ash layer density and ash mass proportion in cake and plug are validated against test data from dynamometer. The model is applied to filters with same brick and different cone designs by modifying cone parameters in GT-Power. The model has been validated for different engine programs over a wide range of test conditions on engine dynamometer and vehicle. The model can be applied for making design decisions like selection of aftertreatment architecture and GPF sizing for the specified engine program and for populating the required pressure drop calibration tables.