Achieving Higher Cleaning Efficiency and Lower Pressure Drop Across a Chocked DPF by Dosing Amino-ethanol

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With the implementation of the Bharat Stage VI emission norms, the accumulation of ash in the diesel particulate filter (DPF) will pose a serious problem for automotive industries during the operating period. In the future, vehicles equipped with DPF will use a DPF regeneration method to burn the trapped soot. This regeneration process leaves the ashes in the DPF, which causes an increase in the pressure drop in the DPF. Due to this pressure drop the engine power loss, efficiency decrease and fuel consumption increases. It also affects the soot loading capacity and the activity of the catalyst in the catalyzed DPF. The main source of ash is lubricating oil, which is involved in combustion. Lubricant additives are responsible for the formation of metallic ash in the DPF. The secondary source of ash is fuel and engine wear. To study the effect of ash accumulation, the DPF sample is canned by designing proper shell through stuffing and selecting right mat, to maintain proper Gap Bulk Density (GBD). Accelerated ash loading of DPF is carried out with burning a diesel with a 5-10 % (by volume) of lubricating oil. Pressure drop and weight is estimated through actual measurement of fresh as well as ash loaded sample. The modeling of DPF is done in Catia, CFD analysis done in Ansys-Fluent and simulation of the Diesel particulate filter and DPF dosing unit is developed in GT- Power software. The simulation results shows pressure drop varies between 30-50 mbar on different-different RPM. Experiment are conducted by cleaning the ash loaded DPF with Amino-Ethanol dosing unit cleaning system. In this dosing unit system we no need to remove DPF from the vehicle. These cleaning system are compared in terms of high cleaning efficiency and low pressure drop.


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  • Name:
    Yash Lethwala
  • Type of entry:
  • Profession:
  • Yash's favorite design and analysis tools:
  • Yash's hobbies and activities:
    Designing, Research
  • Software used for this entry:
    CATIA, ANSYS, GT-Power
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