This paper deals with the possibility of improving the urea dosage control for the Selective Catalytic Reduction Systems (SCR) of an Euro VI d diesel light commercial vehicle in order to increase (Formula presented.) after-treatment reduction performance. To this aim, first, we assess the effective emissions abatement performance for the appraised diesel vehicle via real-world experimental campaign, carried out according to the Real Driving Emissions (RDE) tests on urban, extra-urban and motorway road sections in Naples, Italy. Based on these real-world data, we derive a parameterized control-oriented model for the SCR system which is, then, exploited for the designing of an alternative urea injection logic which could be able to maximize the (Formula presented.) reduction efficiency while minimizing tailpipe ammonia slip. Specifically, the optimal AdBlue injection rate is designed according to a Nonlinear Model Predictive Control Approach which allows obtaining a proper trade-off between the (Formula presented.) abatement and the urea overdosing problem. The effectiveness of the proposed controller is evaluated by comparing the performance assessed for the appraised SCR system during the experimental tests with the ones achievable if the Euro VI diesel would be equipped with the proposed control strategy. Numerical simulation discloses the effectiveness of the NMPC controller in ensuring improved (Formula presented.) reduction with performance complying with the emissions norms, main in avoiding excessive ammonia slip and in guaranteeing a reduced feed ratio w.r.t. to the standard industrial SCR controller mounted on the vehicle.

Improving the NOx reduction performance of an Euro VI d SCR System in real-world condition via nonlinear model predictive control / Petrillo, A.; Prati, M. V.; Santini, S.; Tufano, F.. - In: INTERNATIONAL JOURNAL OF ENGINE RESEARCH. - ISSN 1468-0874. - 24:3(2023), pp. 823-842. [10.1177/14680874211066217]

Improving the NOx reduction performance of an Euro VI d SCR System in real-world condition via nonlinear model predictive control

Petrillo A.
;
Prati M. V.;Santini S.;Tufano F.
2023

Abstract

This paper deals with the possibility of improving the urea dosage control for the Selective Catalytic Reduction Systems (SCR) of an Euro VI d diesel light commercial vehicle in order to increase (Formula presented.) after-treatment reduction performance. To this aim, first, we assess the effective emissions abatement performance for the appraised diesel vehicle via real-world experimental campaign, carried out according to the Real Driving Emissions (RDE) tests on urban, extra-urban and motorway road sections in Naples, Italy. Based on these real-world data, we derive a parameterized control-oriented model for the SCR system which is, then, exploited for the designing of an alternative urea injection logic which could be able to maximize the (Formula presented.) reduction efficiency while minimizing tailpipe ammonia slip. Specifically, the optimal AdBlue injection rate is designed according to a Nonlinear Model Predictive Control Approach which allows obtaining a proper trade-off between the (Formula presented.) abatement and the urea overdosing problem. The effectiveness of the proposed controller is evaluated by comparing the performance assessed for the appraised SCR system during the experimental tests with the ones achievable if the Euro VI diesel would be equipped with the proposed control strategy. Numerical simulation discloses the effectiveness of the NMPC controller in ensuring improved (Formula presented.) reduction with performance complying with the emissions norms, main in avoiding excessive ammonia slip and in guaranteeing a reduced feed ratio w.r.t. to the standard industrial SCR controller mounted on the vehicle.
2023
Improving the NOx reduction performance of an Euro VI d SCR System in real-world condition via nonlinear model predictive control / Petrillo, A.; Prati, M. V.; Santini, S.; Tufano, F.. - In: INTERNATIONAL JOURNAL OF ENGINE RESEARCH. - ISSN 1468-0874. - 24:3(2023), pp. 823-842. [10.1177/14680874211066217]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/880133
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