Abstract
<div class="section abstract"><div class="htmlview paragraph">Model guided application (MGA) combining physico-chemical internal combustion engine simulation with advanced analytics offers a robust framework to develop and test particle number (PN) emissions reduction strategies. The digital engineering workflow presented in this paper integrates the <i>k</i>inetics &amp; SRM Engine Suite with parameter estimation techniques applicable to the simulation of particle formation and dynamics in gasoline direct injection (GDI) spark ignition (SI) engines. The evolution of the particle population characteristics at engine-out and through the sampling system is investigated. The particle population balance model is extended beyond soot to include sulphates and soluble organic fractions (SOF). This particle model is coupled with the gas phase chemistry precursors and is solved using a sectional method. The combustion chamber is divided into a wall zone and a bulk zone and the fuel impingement on the cylinder wall is simulated. The wall zone is responsible for resolving the distribution of equivalence ratios near the wall, a factor that is essential to account for the formation of soot in GDI SI engines. In this work, a stochastic reactor model (SRM) is calibrated to a single-cylinder test engine operated at 12 steady state load-speed operating points. First, the flame propagation model is calibrated using the experimental in-cylinder pressure profiles. Then, the population balance model parameters are calibrated based on the experimental data for particle size distributions from the same operating conditions. Good agreement was obtained for the in-cylinder pressure profiles and gas phase emissions such as NO<sub>x</sub>. The MGA also employs a reactor network approach to align with the particle sampling measurements procedure, and the influence of dilution ratios and temperature on the PN measurement is investigated. Lastly, the MGA and the measurements procedure are applied to size-resolved chemical characterisation of the emitted particles.</div></div>
Highlights
The work presented in this paper is part of the development of particle measurement procedures to lower the current 23 nm limit down to 10 nm for gasoline direct injection (GDI) spark ignition (SI) engines
Model Guided Application (MGA) comprising physico-chemical simulation and advanced statistics has been formulated as part of the development of measurement procedures to robustly detect emitted particles down to sizes as small as 10 nm
The digital engineering workflow simulates the formation of particles in a gasoline direct injection (GDI) spark ignition (SI) engine generated from combustion as well as fuel wall-impingement, as well as the evolution of the particle population through the exhaust sampling system
Summary
The work presented in this paper is part of the development of particle measurement procedures to lower the current 23 nm limit down to 10 nm for gasoline direct injection (GDI) spark ignition (SI) engines. It entails the fundamental understanding of the particle. It is worth mentioning that these tests are time consuming compared to the average simulation time This provides the motivation to combine advanced data-driven statistics with adequately detailed yet computationally efficient physico-chemical simulators within the engine development programmes
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