Optimization of the ammonia coverage ratio references in diesel engine two-can selective catalytic reduction systems via nonlinear model predictive control

Abstract

In this work, we investigate the driving-cycle-based ammonia coverage ratio reference optimization for diesel engine two-can selective catalytic reduction systems. The ammonia coverage ratio references are the desired profiles of the ammonia coverage ratios. As these desired profiles can be set as the references for the feedback controls, it is important to obtain their optimal values. The model development and system parameter identification for these two catalyst cans are carried out by considering the main chemical reactions inside the catalyst cans and using the experimental data from the US06 test driving cycle. The main advantage of the two-can setup is twofold: the first catalyst can is mainly used to reduce the nitrogen oxides; the second catalyst can is used to adsorb the ammonia emitted from the first can such that the nitrogen oxides are reduced and the undesired ammonia slip is constrained. For high nitrogen oxide conversion, it is intuitively required that the ammonia coverage ratio for the first catalyst can is as high as possible. However, a high ammonia coverage ratio increases the ammonia slip downstream. In order to constrain the ammonia slip downstream, it is expected that the ammonia coverage ratio for the second catalyst can is as low as possible. However, the lower ammonia coverage ratio may not help nitrogen oxide reduction in the second can. Because of the conflict in the ammonia coverage ratios for these two catalyst cans, it is quite interesting and meaningful to study the optimal ammonia coverage ratios. With the developed system models, we propose a nonlinear model predictive control approach to solve the optimization problem. Various cases are studied to investigate the effect of the initial value on the ammonia coverage ratios. Compared with the existing results, the obtained ammonia injection profile which decides the ammonia coverage ratios can achieve much better control performance with respect to the tailpipe nitrogen oxide reduction and ammonia slip.

An ammonia coverage ratio observing and tracking controller: stability analysis and simulation evaluation

“…The identification of the model parameters is performed through the previously obtained experimental data. In the distributed cascade urea-SCR system, identifications of the pre-exponential factors and activation energies of the chemical reactions (with reference to Table 1) are the main task [30]. Thus, in the 4-unit cascade system, there are 24 positive parameters to be identified, such as k des,1 , k des,2 , k des,3 , k des,4 , and k SCR,1 .…”

Tutorial of model-based powertrain and aftertreatment system control design and implementation

“…This modeling deficiency inherently limits the performance of SCR control systems. In [71], [75]- [76], control and optimization methods were developed to achieve approximated SCR ammonia coverage ratio distribution profile control by using two SCR cans connected in series. By inserting sensors in the SCR catalyst or splitting the catalyst into two cans, such SCR control approaches try to control urea dosing rate such that the ammonia coverage ratio of the upstream SCR can be high for high NOx conversion efficiency while keeping the ammonia coverage ratio of the downstream SCR can below a low upper bound to constrain the tailpipe ammonia slip.…”

Nonlinear model predictive control applied to multivariable thermal and chemical control of selective catalytic reduction aftertreatment

“…For this reason, model predictive control (MPC) have shown significant promise when applied to SCR. 12–14 Their natural handling of constraints and transport delays incurred in the chemical SCR system permits operating the SCR plant closer to optimal conditions. This results in improved performance in all respects: NO x removal, ammonia slip, and consumption of urea solution.…”