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Research Papers

A Data-Driven Model Predictive Control Approach to Lean NOx Trap Regeneration

[+] Author and Article Information
Milad Karimshoushtari

Politecnico di Torino,
Turin 10138, Italy
e-mail: milad.karimshoushtari@polito.it

Carlo Novara

Politecnico di Torino,
Turin 10138, Italy
e-mail: carlo.novara@polito.it

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT,AND CONTROL. Manuscript received June 28, 2017; final manuscript received August 28, 2018; published online October 4, 2018. Assoc. Editor: Junmin Wang.

J. Dyn. Sys., Meas., Control 141(1), 011016 (Oct 04, 2018) (9 pages) Paper No: DS-17-1327; doi: 10.1115/1.4041354 History: Received June 28, 2017; Revised August 28, 2018

Lean NOx trap (LNT) is one of the most effective after-treatment technologies used to reduce NOx emissions of diesel engines. One relevant problem in this context is LNT regeneration timing control. This problem is indeed difficult due to the fact that LNTs are highly nonlinear systems, involving complex physical/chemical processes, that are hard to model. In this paper, a novel approach for regeneration timing of LNTs is proposed, allowing us to overcome these issues. This approach, named data-driven model predictive control (D2-MPC), does not require a physical model of the engine/trap system but is based on low-complexity polynomial prediction models, directly identified from data. The regeneration timing is computed through an optimization algorithm, which uses the identified models to predict the LNT behavior. Two D2-MPC strategies are proposed, and tested in a co-simulation study, where the plant is represented by a detailed LNT model, built using the well-known commercial tool AMEsim, and the controller is implemented in matlab/simulink.

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References

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Figures

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Fig. 1

LNT storage and purge reactions

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Fig. 2

amesim/matlab co-simulation

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Fig. 3

Validation of the NOx stored quantity prediction model during the NEDC driving cycle

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Fig. 4

D2-MPC1 scheme for regeneration trigger control

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Fig. 5

D2-MPC2 scheme for regeneration trigger control

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Fig. 6

(a) regeneration trigger, (b) NOx stored quantity (g), (c) LNT input NOx (mg/s), and (d) Tailpipe NOx(mg/s)

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Fig. 7

Cumulative tailpipe NOx emissions

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Fig. 8

Comparison between D2-MPC1 and controller 4

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