A Modeling Study of the Exhaust Flow Rate and Temperature Effects on the Particulate Matter Thermal Oxidation Occurring during the Active Regeneration of a Diesel Particulate Filter 2015-01-1044
Numerical models of aftertreatment devices are increasingly becoming indispensable tools in the development of aftertreatment systems that enable modern diesel engines to comply with exhaust emissions regulations while minimizing the cost and development time involved. Such a numerical model was developed at Michigan Technological University (MTU)  and demonstrated to be able to simulate the experimental data  in predicting the characteristic pressure drop and PM mass retained during passive oxidation  and active regeneration  of a catalyzed diesel particulate filter (CPF) on a Cummins ISL engine.
One of the critical aspects of a calibrated numerical model is its usability - in other words, how useful is the model in predicting the pressure drop and the PM mass retained in another particulate filter on a different engine without the need for extensive recalibration. Towards this objective, data acquired during the active regeneration of a CPF on a John Deere (JD) engine at 2200 and 1500 RPM, each at CPF inlet temperatures of 550, 575, 600 and 625 °C was used to develop calibration parameters for the model  with modified substrate property and geometry parameters for the JD data.
A procedure by which a set of PM thermal oxidation kinetic parameters was calibrated for each data set is described. Results from the model outputs of the performance characteristics obtained from this calibration are presented. Comparisons between the calibration parameters of the same model to the Cummins ISL engine data  and the JD engine data calibration are also shown.
Citation: Premchand, K., Raghavan, K., and Johnson, J., "A Modeling Study of the Exhaust Flow Rate and Temperature Effects on the Particulate Matter Thermal Oxidation Occurring during the Active Regeneration of a Diesel Particulate Filter," SAE Technical Paper 2015-01-1044, 2015, https://doi.org/10.4271/2015-01-1044. Download Citation
Kiran C. Premchand, Krishnan Raghavan, John H. Johnson