DIRECT SIMULTANEOUS MEASUREMENT OF PARTICULATE MATTER AND AMMONIA STORAGE ON COMBINED SELECTIVE CATALYTIC REDUCTION FILTER SYSTEMS USING RADIO FREQUENCY SENSORS

Conference · Mon Jul 23 00:00:00 EDT 2018

OSTI ID:1477839

Ragaller, Paul; Sappok, Alexander; Qiao, Jie; Liu, Xiaojin; Aguilar, Jonathan

Tightening global emissions regulations are motivating interest in the development and implementation of Selective Catalytic Reduction + Filtration (SCRF) systems, which are designed to reduce the concentration of tailpipe particulate matter (PM) and NO_x emissions. These systems allow designers to combine the NO_x reduction capability of an SCR with the filtration capability of a particulate filter on a single unit. Practical implementation of these systems requires reliable measurement and diagnosis of their state – both with respect to trapped particulate matter as well as adsorbed ammonia. Currently, these systems rely on a variety of gas sensors, mounted upstream or downstream of the system, that only provide an indirect inference of the operation state. In this study, a single radio frequency (RF) sensor was used to perform simultaneous measurements of soot loading and ammonia inventory on an SCRF. Several SCRF core samples were tested at varying soot and ash loads in a catalyst reactor bench. Soot levels were measured by monitoring changes in the bulk dielectric properties within the catalyst using the sensor, while ammonia levels were determined by feeding selected regions of the RF spectrum into a pretrained generalized regression neural network model. Results show the RF sensor is able to directly measure the instantaneous ammonia inventory, while simultaneously providing soot loading measurements within 0.5 g/L. These results confirm that simultaneous measurements of both the PM and ammonia loading state of an SCRF are possible using a single RF sensor via analysis of specific features in the full RF spectrum. The results indicate significant potential to remove the control barriers typically associated with the implementation of advanced SCRF systems.

• Research Organization: Filter Sensing Technologies, Inc., Malden, MA (United States)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Vehicle Technologies Office (EE-3V)
• DOE Contract Number: EE0007214
• OSTI ID: 1477839
• Report Number(s): ICEF2018-9528
• Resource Relation: Conference: ASME 2018 Internal Combustion Fall Technical Conference ICEF2018, San Diego, California, USA, November 4-7, 2018
• Country of Publication: United States
• Language: English