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A Model Based Approach to DPF Soot Estimation and Validation for BSVI Commercial Vehicles in Context to Indian Driving Cycles
ISSN: 0148-7191, e-ISSN: 2688-3627
Published September 22, 2021 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
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.
Data Sets - Support Documents
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- Warner , J. , Dobson , D. , and Cavataio , G. A Study of Active and Passive Regeneration Using Laboratory Generated Soot on a Variety of SiC Diesel Particulate Filter Formulations SAE Int. J. Fuels Lubr. 3 1 2010 149 164 https://doi.org/10.4271/2010-01-0533
- Boger , T. , Rose , D. , Tilgner , I. , and Heibel , A. Regeneration Strategies for an Enhanced Thermal Management of Oxide Diesel Particulate Filters SAE Int. J. Fuels Lubr. 1 1 2009 162 172 https://doi.org/10.4271/2008-01-0328
- Rose , D. and Boger , T. Different Approaches to Soot Estimation as Key Requirement for DPF Applications SAE Technical Paper 2009-01-1262 2009 https://doi.org/10.4271/2009-01-1262
- Gaiser , G. and Mucha , P. Prediction of Pressure Drop in Diesel Particulate Filters Considering Ash Deposit and Partial Regenerations SAE Technical Paper 2004-01-0158 2004 https://doi.org/10.4271/2004-01-0158
- Barba , F. , Vassallo , A. , and Greco , V. Estimation of DPF Soot Loading through Steady-State Engine Mapping and Simulation for Automotive Diesel Engines Running on Petroleum-Based Fuels SAE Technical Paper 2017-24-0139 2017 https://doi.org/10.4271/2017-24-0139