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Verifying the Efficiency of a Diesel Particulate Filter Using Particle Counters with Two Different Measurements in Periodic Technical Inspection of Vehicles

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  • Wojciech Jarosiński

    (Motor Transport Institute, 03-301 Warsaw, Poland)

  • Piotr Wiśniowski

    (Motor Transport Institute, 03-301 Warsaw, Poland)

Abstract

The article presents the possibility of verifying the efficiency of a diesel particulate filter (DPF) with the use of particle counters using two different measurement methods. The tests were carried out at a vehicle inspection station using a condensation particle counter (CPC) and a diffusion charger (DC). This article presents the results of measurements of 50 vehicles. Removal of the diesel particulate filter from a vehicle is prohibited but is a known phenomenon throughout the EU. The task of periodic technical inspections is to eliminate vehicles that are inoperative and do not meet the environmental protection requirements. However, to date, European vehicle inspection stations do not have an effective tool to counter tampering with diesel particulate filters. The performed measurements allowed us to prove the hypothesis that both methods of measurement allow the effective confirmation of the presence of DPF in a vehicle during the periodic technical inspection of the vehicle and verification of the quality of its operation. In addition, the advantages and disadvantages of both measurement methods were assessed.

Suggested Citation

  • Wojciech Jarosiński & Piotr Wiśniowski, 2021. "Verifying the Efficiency of a Diesel Particulate Filter Using Particle Counters with Two Different Measurements in Periodic Technical Inspection of Vehicles," Energies, MDPI, vol. 14(16), pages 1-12, August.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:16:p:5128-:d:617801
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    References listed on IDEAS

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    1. Silitonga, A.S. & Masjuki, H.H. & Ong, Hwai Chyuan & Sebayang, A.H. & Dharma, S. & Kusumo, F. & Siswantoro, J. & Milano, Jassinnee & Daud, Khairil & Mahlia, T.M.I. & Chen, Wei-Hsin & Sugiyanto, Bamban, 2018. "Evaluation of the engine performance and exhaust emissions of biodiesel-bioethanol-diesel blends using kernel-based extreme learning machine," Energy, Elsevier, vol. 159(C), pages 1075-1087.
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