Development and Implementation of a Mapless, Model Based SCR Control System

Authors Abstract
Content
Various engine platforms employ Selective Catalytic Reduction (SCR) technology to reduce the tail pipe emissions of oxides of nitrogen (NOx) from diesel engines as part of an overall strategy to comply with the emission regulations in place in various countries. High levels of NOx conversion (greater than 98%) in SCR aftertreatment may provide operating margin to increase overall fuel efficiency. However, to realize the potential fuel efficiency gains, the SCR technology employed should achieve high NOx conversion with limited reductant slip over transient application cycles in addition to steady state operation.
A new approach to SCR controls was developed and implemented. This approach does not rely on any maps to determine the amount of urea solution to be dosed, thus significantly reducing calibration and development time and effort when implementing the SCR technology on multiple engine platforms and applications.
In addition, the controls technique is completely model based and was able to achieve high NOx conversion efficiencies through the SCR system, while ensuring limited ammonia slip due to sharp transient events in the application cycle. This ability allows the system to extract the maximum performance from the SCR catalyst, enabling the catalyst size to be optimized for space and cost constraints.
The successful implementation of this control technique requires an SCR model with prediction accuracies greater than that typically achieved in practical implementation. Therefore, a real time correction technique was used to enhance the model accuracy to the desired levels for use in the controls algorithm.
Meta TagsDetails
DOI
https://doi.org/10.4271/2014-01-9050
Pages
12
Citation
Chavannavar, P., "Development and Implementation of a Mapless, Model Based SCR Control System," SAE Int. J. Engines 7(2):1113-1124, 2014, https://doi.org/10.4271/2014-01-9050.
Additional Details
Publisher
Published
Jul 1, 2014
Product Code
2014-01-9050
Content Type
Journal Article
Language
English