IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v333y2025ics0360544225031111.html
   My bibliography  Save this article

Sustainable diesel engine performance enhancement using pyrolytic plastic oil blends: experimental investigation and artificial neural network-based prediction

Author

Listed:
  • Dutta, Sarajit
  • Khan, Muhammad Neamat Ullah
  • Hoque, Md Emdadul
  • Jin, Yingai
  • Alam, Firoz
  • Trinuruk, Piyatida

Abstract

This paper presents the use of pyrolytic plastic oil (PPO) blends in single-cylinder, water-cooled diesel engines, analyzing their performance across various loading conditions. PPO was produced via pyrolysis of waste plastics, with HDPE being the dominant material. Five different fuel blends were created by varying volumetric ratios, and their physical properties were analyzed, showing similarities with pure diesel. Chemical characterizations through FTIR and UV–Vis spectroscopy confirmed the presence of aromatics, conjugated bonds and oxygenated compounds in PPO blends, influencing engine performance. Results demonstrated improved brake thermal efficiency (BTE) with higher blend ratios, though knocking tendency increased at peak loads. The PPO40 blend demonstrated optimal performance across all conditions. An artificial neural network (ANN) model was developed using experimental data, with engine load and blend ratios as input features and output parameters including brake specific fuel consumption (BSFC), BTE, exhaust gas temperature (EGT), and brake mean effective pressure (BMEP). The model demonstrated excellent accuracy in predicting engine performance, with statistical consistency validated against experimental results. The model's ability to predict outcomes for an untested intermediate blend (PPO70) across load conditions highlights its strength as a predictive tool. Additionally, factors affecting performance, such as concentration of chemical functional groups, were discussed in comparison with pure diesel. This research validates the potential of PPO as an alternative fuel for CI engines, offering a sustainable solution to reduce reliance on fossil fuels.

Suggested Citation

  • Dutta, Sarajit & Khan, Muhammad Neamat Ullah & Hoque, Md Emdadul & Jin, Yingai & Alam, Firoz & Trinuruk, Piyatida, 2025. "Sustainable diesel engine performance enhancement using pyrolytic plastic oil blends: experimental investigation and artificial neural network-based prediction," Energy, Elsevier, vol. 333(C).
  • Handle: RePEc:eee:energy:v:333:y:2025:i:c:s0360544225031111
    DOI: 10.1016/j.energy.2025.137469
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544225031111
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2025.137469?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:333:y:2025:i:c:s0360544225031111. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.