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

Abstract The selective catalytic reduction (SCR) technology is a promising diesel after-treatment technology due to its high NO x reduction potential. A nonlinear model predictive control (NMPC) approach was proposed based on the three-state SCR model here for control and optimization of SCR system to maximize NO x reduction while minimizing NH 3 slip and urea consumption; moreover, the ammonia coverage ratio was designed to as a control target, whose desired range was obtained by means of the singular perturbation method, that is to say, the upper limit of ammonia coverage ratio was derived by 10 ppm NH 3 slip while the lower limit was calculated by maximum NO x conversion efficiency, which was obtained through a novel model based non-dominated sorting genetic algorithm (NSGA-II) according to an optimum tradeoff between NO x conversion and NH 3 slip at each engine operating point. The state-feedback NMPC algorithm was applied to ensure the estimated ammonia coverage ratio falling in the desired range so that the SCR performance can be optimized over entire engine operating. The standard European steady-state cycle (ESC) was performed for data generation from a diesel engine equipped with a commercial SCR and to verify the effectiveness of the designed control strategy. Simulation results over the entire ESC indicated that the NO x conversion efficiency may be optimal in various engine operating modes and the NMPC controller ensures the most part of the cycle may conform to the NO x emissions requirements; moreover, the downstream NH 3 concentration was less than the limit; especially, the whole mean NH 3 slip was 9.7 ppm which is basically close to the given limit (10 ppm); furthermore, the ammonia storage capacity falls rapidly along with growth of the temperature but the NMPC still worked well for prevention of any unacceptably high NH 3 slip. The experimental verification was carried out and the results showed that the designed strategy was effective and acceptable compared with the simulated results.

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