Nox conversion efficiency optimization based on NSGA-II and state-feedback nonlinear model predictive control of selective catalytic reduction system in diesel engine

Li, Wei; Yan, Fuwu; Hu, Jie; Xi, Guangwei; Liu, Bo

doi:10.1016/j.apenergy.2017.08.223

Cited by 38 publications

(15 citation statements)

References 41 publications

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“…Nitrogen oxides (NO x ) present significant environmental challenges as important pollutants. [1][2][3] To mitigate NO x emissions from stationary sources such as thermal power plants and the iron and steel industry, selective catalytic reduction (SCR) technology employing NH 3 as a reductant has gained widespread use. 4 The exploration of lowtemperature NH 3 -SCR technology has been a focal point of research.…”

Section: Introductionmentioning

confidence: 99%

Modulating active oxygen species on α-MnO₂ with K and Pb for SCR of NO at low temperatures

Yang,

Luo,

Liu

et al. 2023

Catal. Sci. Technol.

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Section: Introductionmentioning

confidence: 99%

Modulating active oxygen species on α-MnO₂ with K and Pb for SCR of NO at low temperatures

Yang,

Luo,

Liu

et al. 2023

Catal. Sci. Technol.

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“…Although the accurate modeling of SCR system, the real-time implementation of control strategies involving the PDEs requires a greater computational effort. 40 By leveraging, instead, model-based non-dominated sorting genetic algorithm (NSGA-II) to determine desired range for ammonia coverage ratio at SCR, 41,42 proposes a NMPC algorithm. Note that desired ammonia corage ration is estimated in real-time and this results an in increasing of the computational effort required by the overall control system architecture.…”

Section: Introductionmentioning

confidence: 99%

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

Petrillo

Prati²,

Santini

et al. 2021

International Journal of Engine Research

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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.

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“…To satisfy these strict requirements, various NOx reduction technologies are being continuously studied. Typically, exhaust after-treatment technologies, such as exhaust gas recirculation (EGR) and selective catalytic reduction (SCR), are the main options for ship manufacturers to ensure their environmental requirements [2][3][4][5][6][7][8][9]. The SCR method is the most effective for reducing NOx emissions using the urea-water solution.…”

Section: Introductionmentioning

confidence: 99%

A Study on the Predictive Maintenance Algorithms Considering Load Characteristics of PMSMs to Drive EGR Blowers for Smart Ships

Kim¹

2021

Energies

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Exhaust gas recirculation (EGR) is a NOx reduction technology that can meet stringent environmental regulatory requirements. EGR blower systems must be used to increase the exhaust gas pressure at a lower rate than the scavenging air pressure. Electric motor drive systems are essential to rotate the EGR blowers. For the effective management of the EGR blower systems in smart ships, there is a growing need for predictive maintenance technology fused with information and communication technology (ICT). Since an electric motor accounts for about 80% of electric loads driven by the EGR, it is essential to apply the predictive maintenance technology of the electric motor to maximize the reliability and operation time of the EGR blower system. Therefore, this paper presents the predictive maintenance algorithm to prevent the stator winding turn faults, which is the most significant cause of the electrical failure of the electric motors. The proposed algorithm predicts the remaining useful life (RUL) by obtaining the winding temperature value by considering the load characteristics of the electric motor. The validity of the proposed algorithm is verified through the simulation results of an EGR blower system model and the experimental results derived from using a test rig.

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Nox conversion efficiency optimization based on NSGA-II and state-feedback nonlinear model predictive control of selective catalytic reduction system in diesel engine

Cited by 38 publications

References 41 publications

Modulating active oxygen species on α-MnO₂ with K and Pb for SCR of NO at low temperatures

Modulating active oxygen species on α-MnO₂ with K and Pb for SCR of NO at low temperatures

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

A Study on the Predictive Maintenance Algorithms Considering Load Characteristics of PMSMs to Drive EGR Blowers for Smart Ships

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Nox conversion efficiency optimization based on NSGA-II and state-feedback nonlinear model predictive control of selective catalytic reduction system in diesel engine

Cited by 38 publications

References 41 publications

Modulating active oxygen species on α-MnO2 with K and Pb for SCR of NO at low temperatures

Modulating active oxygen species on α-MnO2 with K and Pb for SCR of NO at low temperatures

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

A Study on the Predictive Maintenance Algorithms Considering Load Characteristics of PMSMs to Drive EGR Blowers for Smart Ships

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Modulating active oxygen species on α-MnO₂ with K and Pb for SCR of NO at low temperatures

Modulating active oxygen species on α-MnO₂ with K and Pb for SCR of NO at low temperatures

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