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

2021 ◽  
pp. 146808742110662
Author(s):  
Alberto Petrillo ◽  
Maria Vittoria Prati ◽  
Stefania Santini ◽  
Francesco Tufano

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: see text] 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: see text] 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: see text] 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: see text] 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.

Author(s):  
Ming-Feng Hsieh ◽  
Junmin Wang ◽  
Marcello Canova

This paper describes a two-level nonlinear model predictive control (NMPC) scheme for diesel engine lean NOx trap (LNT) regeneration control. Based on the physical insights into the LNT operational characteristics, a two-level NMPC architecture with the higher-level for the regeneration timing control and the lower-level for the regeneration air to fuel ratio profile control is proposed. A physically based and experimentally validated nonlinear LNT dynamic model is employed to construct the NMPC control algorithms. The control objective is to minimize the fuel penalty induced by LNT regenerations while keeping the tailpipe NOx emissions below the regulations. Based on the physical insights into the LNT system dynamics, different choices of cost function were examined in terms of the impacts on fuel penalty and tailpipe NOx slip amount. The designed control system was evaluated on an experimentally validated vehicle simulator, cX-Emissions, with a 1.9 l diesel engine model through the FTP75 driving cycle. Compared with a conventional LNT control strategy, 31.9% of regeneration fuel penalty reduction was observed during a single regeneration. For the entire cold-start FTP75 test cycle, a 28.1% of tailpipe NOx reduction and 40.9% of fuel penalty reduction were achieved.


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