Estimation of DPF Soot Loading through Steady-state Engine Mapping and Simulation for Automotive Diesel Engines Running on Petroleum-Based Fuels

Paper #:
  • 2017-24-0139

  • 2017-09-04
The aim of the present study is to improve the effectiveness of the engine and aftertreatment calibration process through the critical evaluation of several methodologies available to estimate the soot mass flow produced by diesel engines and filtered by Diesel Particulate Filters (DPF). In particular, the focus of the present study has been the development of a reliable simulation method for the accurate prediction of the engine-out soot mass flow starting from Filter Smoke Number (FSN) measurements executed in steady state conditions, in order to predict the DPF loading considering different engine working conditions corresponding to NEDC and WLTP cycles. In order to achieve this goal, the study was split into two parts: - Correlation between ‘wet soot’ (measured by soot filter weighing) and the ‘dry soot’ (measured by the Micro Soot Sensor MSS). For this purpose, test activities have been carried out taking into account different boundaries conditions such as calibration, driving cycle, sampling probes positions; - Identification of a reliable and accurate method that allows estimating the ‘dry soot’ starting from the FSN measurements. Different equations available in literature have been investigated. Finally it has been selected the most reliable and accurate one which allows to better correlate the simulation output with the MSS sensor measurement over different test cycles. The output of the study is the definition of a simulation method which has proved accurate and exhibited a good correlation with the reference technique used in the literature, the soot filter weighting. Furthermore, the test activities conducted lead the authors to the evaluation of a best practice for the soot measurement in both steady-state and transient conditions, including sampling probes installation. This best practice is suggested in order to measure reliable data during the test activities and, avoid inconsistencies during the engine development phases.
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