On- Board Diagnosis of Improper Reductant Detection in BS6 SCR System Using Virtual Sensor Modelling

2024-26-0256

01/16/2024

Event
Symposium on International Automotive Technology
Authors Abstract
Content
Selective Catalytic Reduction (SCR) is an optimized technology developed to encounter current BS6 Emission Regulations. AdBlue is the reductant used in the SCR Dosing system to eliminate NOx in the Exhaust gas. In order to ensure engine emissions compliance, insufficient or improper reductant in tank required to be detected. The right AdBlue concentration of 32.5% is highly necessary to attain the higher NOX conversion efficiency. Low concentration of the reductant will drastically reduce the NOx conversion in the system. Hence monitoring the AdBlue concentration in the tank itself is more important as per the OBD legislation. This implies on a physical quality sensor in the tank for detecting the reductant concentration. The functionalities of the quality sensor can also be instituted via a virtual software modelling called Improper Reductant Detection (IRD). IRD logic is highly robust and work competently to meet the BS6 stage 2 legislation’s NOx target. The reductant is suspected after each tank refill event, automatically IRD logic runs in the software in general, but the routine is started only if the NOx conversion efficiency is getting worse as well. The approach is to increase the AdBlue dosing rate if there is a suspicion of an improper reductant. The comparison of the NOx conversion efficiency before and after increasing dosing determines whether the reductant is good or not. Henceforth, the component failure of high-cost Quality sensor can be prevented and improvised through a software model that promises a low-cost solution to the product which in turn benefits the customer.
Meta TagsDetails
DOI
https://doi.org/10.4271/2024-26-0256
Pages
4
Citation
M, J., K, S., and YS, A., "On- Board Diagnosis of Improper Reductant Detection in BS6 SCR System Using Virtual Sensor Modelling," SAE Technical Paper 2024-26-0256, 2024, https://doi.org/10.4271/2024-26-0256.
Additional Details
Publisher
Published
Jan 16
Product Code
2024-26-0256
Content Type
Technical Paper
Language
English