After-treatment sensors are used in the ECU feedback control to calibrate the engine operating parameters. Due to their contact with exhaust gases, especially NOx sensors are prone to soot deposition with a consequent decay of their performance. Several phenomena occur at the same time leading to sensor contamination: thermophoresis, unburnt hydrocarbons condensation and eddy diffusion of submicron particles. Conversely, soot combustion and shear forces may act in reducing soot deposition. This study proposes a predictive 3D-CFD model for the analysis of the development of soot deposition layer on the sensor surfaces. Alongside with the implementation of deposit and removal mechanisms, the effects on both thermal properties and shape of the surfaces are taken in account. The latter leads to obtain a more accurate and complete modelling of the phenomenon influencing the sensor overall performance. The evolution of the fouling thickness is evaluated by means of the implementation of a morphing and remesh procedure based on the local conditions of both the flow and the pollutant concentration. The proposed model was tested on actual sensors by means of accelerated contamination cycles. The sensor behavior was correlated to the experimental response time to account for the decay of performance due to fouling accumulation. The response time is calculated both in the middle of the contamination cycle and at its end. Comparing the experimental data with the CFD results an error lower than the 9% is obtained.

Predictive 3D-CFD Model for the Analysis of the Development of Soot Deposition Layer on Sensor Surfaces / D'Orrico, F.; Cicalese, G.; Breda, S.; Fontanesi, S.; Cozza, I.; Tosi, S.; Gopalakrishnan, V.. - In: SAE TECHNICAL PAPER. - ISSN 0148-7191. - (2023). (Intervento presentato al convegno SAE 16th International Conference on Engines and Vehicles, ICE 2023 tenutosi a Capri, ita nel 10-14 settembre 2023) [10.4271/2023-24-0012].

Predictive 3D-CFD Model for the Analysis of the Development of Soot Deposition Layer on Sensor Surfaces

Cicalese G.;Breda S.;Fontanesi S.;
2023

Abstract

After-treatment sensors are used in the ECU feedback control to calibrate the engine operating parameters. Due to their contact with exhaust gases, especially NOx sensors are prone to soot deposition with a consequent decay of their performance. Several phenomena occur at the same time leading to sensor contamination: thermophoresis, unburnt hydrocarbons condensation and eddy diffusion of submicron particles. Conversely, soot combustion and shear forces may act in reducing soot deposition. This study proposes a predictive 3D-CFD model for the analysis of the development of soot deposition layer on the sensor surfaces. Alongside with the implementation of deposit and removal mechanisms, the effects on both thermal properties and shape of the surfaces are taken in account. The latter leads to obtain a more accurate and complete modelling of the phenomenon influencing the sensor overall performance. The evolution of the fouling thickness is evaluated by means of the implementation of a morphing and remesh procedure based on the local conditions of both the flow and the pollutant concentration. The proposed model was tested on actual sensors by means of accelerated contamination cycles. The sensor behavior was correlated to the experimental response time to account for the decay of performance due to fouling accumulation. The response time is calculated both in the middle of the contamination cycle and at its end. Comparing the experimental data with the CFD results an error lower than the 9% is obtained.
2023
SAE 16th International Conference on Engines and Vehicles, ICE 2023
Capri, ita
10-14 settembre 2023
D'Orrico, F.; Cicalese, G.; Breda, S.; Fontanesi, S.; Cozza, I.; Tosi, S.; Gopalakrishnan, V.
Predictive 3D-CFD Model for the Analysis of the Development of Soot Deposition Layer on Sensor Surfaces / D'Orrico, F.; Cicalese, G.; Breda, S.; Fontanesi, S.; Cozza, I.; Tosi, S.; Gopalakrishnan, V.. - In: SAE TECHNICAL PAPER. - ISSN 0148-7191. - (2023). (Intervento presentato al convegno SAE 16th International Conference on Engines and Vehicles, ICE 2023 tenutosi a Capri, ita nel 10-14 settembre 2023) [10.4271/2023-24-0012].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1372176
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