Browse Topic: Particulate filters
The current and upcoming Internal Combustion Engine (ICE) emission norms are very stringent. It is difficult to meet emission standards with just combustion optimization techniques. As a result, post-treatment is required for Engine-out emissions. Otherwise, these hazardous gases impact the ecosystem of living beings. Many technologies are implemented at the exhaust for reducing the emissions. Diesel Particulate Filter (DPF) is one such technique to achieve lower Particulate Matter (PM) and Particulate Number (PN) emission goals. In order to achieve such emission reduction, the DPF undergoes periodic cleaning called regeneration. During regeneration, the exhaust systems including DPF are maintained at elevated temperatures to achieve proper cleaning. When the vehicle is in regeneration, sudden braking or accelerator pedal release leads to engine Drop to Idle speeds (DTI), which sharply increases the temperature gradient inside the DPF which may result in physical damage like cracks
Diesel Particulate Filters (DPFs) have been used extensively worldwide as a Particle Mass (PM) / Particle Number (PN) reduction technology for various diesel applications. Based on CARB’s latest Tier 5 regulation workshop, PM emission targets are expected to become a lot more stringent; from 0.02 g/kWh to 0.005 g/kWh (75% reduction compared to Tier 4 Final (Tier 4f)). Also, CO2 emission targets are expected to be introduced for Tier 5. In parallel, EU Stage VI emission regulation standards and implementation timing could be announced sometime in late 2024. It is expected that PN emission standards will be tightened such as extending measurement range of PN from 23 nm to 10 nm. With Tier 5 and EU Stage VI regulations approaching, several OEMs are considering implementing a common aftertreatment system that can meet emission targets for both regions. High filtration efficiency and low backpressure DPFs will be required to meet PM/PN and CO2 emission standards. NGK has developed several
The automobile industry is going through one of the most challenging times, with increased competition in the market which is enforcing competitive prices of the products along with meeting the stringent emission norms. One such requirement for BS6 phase 2 emission norms is monitoring for partial failure of the component if the tailpipe emissions are higher than the OBD limits. Recently PM (soot) sensor is employed for partial failure monitoring of DPF in diesel passenger cars.. PM sensor detects soot leakage in case of DPF substrate failure. There is a cost factor along with extensive calibration efforts which are needed to ensure sensor works flawlessly. This paper deals with the development of an algorithm with which robust detection of DPF substrate failure is achieved without addition of any sensor in the aftertreatment system. In order to achieve this, a thermodynamic model of DPF substate was created using empirical relations between parameters like exhaust flow rate, exhaust
With the implementation of BS6 Norms, there is an increased focus on reducing particulate matter emissions from gasoline Direct Injection (GDI) engines. GPFs are effective in capturing particulate matter (PM) and particulate number (PN) but their calibration is critical to ensure optimal performance and emissions compliance. This paper presents a study on the calibration of Gasoline Particulate Filters (GPF) to comply with Bharat Stage-6 (BS6) emissions norms. The focus is on thermal management, soot loading, ash loading, and the unique challenges faced in the Indian market. Thermal management strategies include active and passive methods to optimize GPF regeneration and prevent thermal degradation. Soot load detection involves engine-out simulation-based approach as well as delta-Pressure-based approach for accurate soot modelling. Impact of ash loading and its effects on filtration efficiency and pressure drop will also be discussed. Further the strategies to overcome the challenges
Recent legislations require very low soot emissions downstream of the particulate filter in diesel vehicles. It will be difficult to meet the new more stringent OBD requirements with standard diagnostic methods based on differential sensors. The use of inexpensive and reliable soot sensors has become the focus of several academic and industrial works over the past decade. In this context, several diagnostic strategies have been developed to detect DPF malfunction based on the soot sensor loading time. This work proposes an advanced online diagnostic method based on soot sensor signal projection. The proposed method is model-free and exclusively uses soot sensor signal without the need for subsystem models or to estimate engine-out soot emissions. It provides a comprehensive and efficient filter monitoring scheme with light calibration efforts. The proposed diagnostic algorithm has been tested on an experimentally validated simulation platform. 2D signatures are generated from soot
A multi-functional membrane filter was developed through deposition of agglomerated Three-Way Catalyst particles with a size of 1 ~ 2 microns on the conventional bare particulate filter. The filtration efficiency reaches almost 100 % from the beginning of soot trapping with a low pressure drop and both reductions of NO and CO emission were achieved.
This research aimed to improve the PN filtration efficiency of a catalyst coated gasoline particulate filter (cGPF) to meet the next generation of emissions regulations for internal combustion engines. This paper proposes a concept that improves the PN filtration performance while maintaining low pressure drop by forming a thin PM trap layer on the surface of the cGPF substrate. The design guidelines for the coating particle size and coating amount of the PM trap layer were investigated, and actual manufacturing issues were also identified. The validity of this concept and guidelines was then verified on an actual vehicle.
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