A Model Based Approach to DPF Soot Estimation and Validation for BSVI Commercial Vehicles in Context to Indian Driving Cycles 2021-26-0183

With India achieving the BSVI milestone, the diesel particulate filter (DPF) has become an imperative component of a modern diesel engine. A DPF system is a device designed to trap soot from exhaust gas of the diesel engine and demands periodic regeneration events to oxidize the accumulated soot particles. The regeneration event is triggered either based on the soot mass limit of the filter or the delta pressure across it. For a Heavy Duty Diesel Engine (HDDE), pressure difference across the DPF is not usually reliable as the size of the DPF is large enough compared to the DPF used ina passenger vehicle diesel engine. Also, the pressure difference across DPF is a function of exhaust mass flow and thus it makes it difficult to make an accurate call for active regeneration. This demands for a very accurate soot estimation model and it plays a vital role in a successful regeneration event.

This paper describes about a soot estimation model developed from an empirical engine out soot emissions model, combined with a physical soot oxidation model to determine the soot load in the DPF. MATLAB/Simulink model was developed to provide an actual soot mass value deposited in the DPF under all Indian driving conditions - from a low load low speed city cycle to a high load high speed highway cycle. A novel attempt is made to front load the soot modelling calibration on test bed by covering all possible Indian terrains by considering atmospheric pressure up to 82kPa and inlet air temperature up to 30°C using Simulink model. Final verification trials were done by actually running the vehicle on different duty cycles. The Simulink model could achieve an accuracy of ±15% against actual soot load in the DPF for all driving cycles. With the help of such model, the calibration effort could be greatly reduced as more number of driving cycles could be validated in a short time which was the greatest challenge to achieve BSVI targets.