Semi-empirical model for indirect measurement of soot size distributions in compression ignition engines

Abstract

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In-cylinder pressure smart sampling for efficient data management

“…5,6 The resonance intensity is frequently estimated through the maximum amplitude pressure oscillation (MAPO) and it can be useful to identify the levels of vibration and even maintain the knock occurrence with stochastic controls in desired levels. 7,8 The in-cylinder pressure signal can be used as input to feed several models that estimate other control parameters, such as in Khameneian et al 9 to estimate the temperature and air distribution for a GDI spark ignition engine, in Muric´et al 10 to estimate the emitted NOx from the HRR and the unburned temperature, in d'Ambrosio et al 11 to estimate the combustion noise, in Bares et al 12 to predict the knock probability, in Broatch et al 13 and Youssef 14 to estimate the trapped mass, or in Martos et al 15 to estimate the soot by semiempirical models. These models can be used to replace current sensors, to improve the accuracy of the estimation in a sensor data fusion scenario, 16 or to identify the system dynamics in order to design advanced controls.…”

Soot Precursors Analysys Using Detailed Chemical Kinetic Mechanisms in an Ethylene/Air Laminar Diffusion Flame

“…As highlighted by the multi-moment sectional method (Yang and Mueller, 2019), in which statistical moments are computed for each domain section, hybridization of the referred soot modeling approaches is possible as well. Since the utilization of less general semi-empirical models involves a relatively low computational cost, its use in recent years has been mainly limited to complex applications, including turbulent flows (Reddy et al, 2016;Snegirev et al, 2018), practical compression ignition engines (Martos et al, 2018), and laminar flows including detailed chemistry (Johnson et al, 2020). Detailed soot formation models can be also used in similar applications but the computational cost is comparatively higher.…”