“Real-Time Estimation of Soot for a Wall Flow DPF Regeneration Management and an Efficient DOE for Model Calibration.” 2021-26-0333

Estimation of soot deposited on a wall flow type DPF, is a vital information to ensure safe and efficient DPF management. Accuracy in determining mass of soot present inside the DPF ensures a correct regeneration management strategy in-terms of fuel efficiency and DPF safety considering soot overloading and too frequent regenerations. It also ensures an efficient detection of anomalies in the PM filtration mandated by the BSVI/EURO VI legislation as a part of On-board diagnostics. Classical approach of determining soot present inside DPF involves monitoring increase in pressure drop. Real time usage of such a model is limited by the inaccuracy of measuring pressure drop at low exhaust flows. Hence, contemporary engine controllers use pressure drop based models as a failsafe and estimate DPF soot loading by modelling soot release rate due to engine combustion and the rate at which it is oxidized. Determination of soot release rate depends on a plethora of aspects starting from engine operation to EGR rates to AFR etc. Similarly, soot oxidation rate depends on exhaust temperature, NO2/O2 content of exhaust, space velocity of exhaust etc. Due to dependency on high number of parameters, calibration of such a control algorithm for a road worthy vehicle is significantly long and iterative process. Unless a carefully designed DOE is followed, the entire process of calibrating soot load estimation models could consume an exorbitant amount of resource and time. This paper describes fundamental aspects of a soot load estimation model and more importantly discusses about a structured testing and calibration methodology as a design of experiment (DOE) that has proven to be extremely efficient. Importance of determining soot saturation in DPF (where soot in-flow due to combustion is balanced by passive regeneration rates), for fast and efficient calibration of soot load algorithm is explained along with the above-mentioned DOE.