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The BS6 norms (phase 1) were implemented in India from April 1, 2020 and replaced the previous BS4 norms. Phase 2 of the BS6 norms, which came into effect on April 1, 2023. In accordance with the regulation requirement, effective performance of after treatment systems like DPF and SCR demands critical hardware implementation and robust monitoring strategies in the extended operating zone. Effective OBD monitoring of DPF, which is common to all BSVI certified vehicles, such that the defined strategy detects the presence or absence of the component is imperative. A robust monitoring strategy is developed to detect the presence of the DPF in the real world incorporating the worst possible driving conditions including idling, and irrespective of other environmental factors subject to a location or terrain. The differential pressure sensor across the DPF is used to study the actual pressure drop across the DPF.

The adoption of BSVI emission norms for Indian domestic market brought a very stringent window for pollutants. For CI engines, the major impact was in the reduction of NOx by 68% and PM by 82% from BSIV norms. Technologically advanced after treatment systems like SCR / DPF / LNT aid to meet the stringent emission norms. Implementation of high-end after treatment systems in vehicles, requires precise monitoring and fool proof feedback systems. On Board Diagnostics (OBD) makes this possible. OBD is used to monitor the performance of after treatment systems and warn the user in case of deterioration. The challenges in framing OBD strategy increases with more electronic hardware and complex algorithms taking control, to monitor precise information on system performance. For a fool proof OBD monitoring of the exhaust system, a complete understanding of the SCR system and its components in terms of hardware specifications and software functionality is critical.

Selective Catalytic Reduction is a key technology, used for NOx abatement. There are several models available for SCR system performance out of which most are experimentally verified only in flow reactors with simulated gaseous concentration and standard test conditions. But in the vehicle as well as in the engine test bench the conditions are very much dynamic compared to the simulated conditions of the lab. This transient behaviour emphasizes the need for a best fit model which accommodates the real-world dynamic conditions, thus reducing the overall effort in SCR catalyst selection for any given engine or vehicle application. The primary objective of this paper is to derive an empirical and mathematical efficiency model for SCR catalyst performance through a model-based design approach. The output from the model is compared with the experimental results from the vehicle and engine test bench, to validate the model accuracy.