An Adaptive Proportional Integral Control of a Urea Selective Catalytic Reduction System based on System Identification Models

For urea Selective Catalytic Reduction (SCR) systems, adaptive control is of interest to provide a capability of maintaining high NO_x conversion efficiency and low ammonia slip in the presence of uncertainties in the system. In this paper, the dynamics of the urea SCR system are represented by a control-oriented model which is based on a linear transfer function, with parameters dependent on engine operating conditions. The parameters are identified from input-output data generated by a high fidelity full chemistry model of the urea SCR system. The use of the full chemistry model facilitated the representation of the dynamics of stored ammonia (not a directly measurable parameter) as well as post SCR NO_x and ammonia slip.

A closed-loop Proportional-plus-Integral (PI) controller was first designed using the estimate of stored ammonia as a feedback signal. The performance was evaluated using the full chemistry model, and was shown to result in a NO_x conversion efficiency of over 95%, with a maximum NH₃-slip of less than 5 ppm. An adaptive PI controller was then designed and tested, and was shown to lead to comparable performance. By incorporating nonlinear components and projection maps which accounted for the nonlinear relationship between stored ammonia and post SCR sensor measurement, the adaptive controller was extended to a variant that directly uses the sensor measurements (responsive to both NO_x-slip and ammonia slip). This novel adaptive PI-controller was simulated on the full chemistry model, and shown to be capable of delivering over 90% of NO_x conversion efficiency at a peak ammonia slip of less than 2 ppm. Experimental results from a test vehicle demonstrated that as adaptation proceeds, efficiency of SCR increases to levels of 90%, when driven in city traffic, with a mean ammonia slip of about 10 ppm.