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Predictive Models for Biodiesel Performance and Emission Characteristics in Diesel Engines: A Review

Author

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  • Wenbo Ai

    (Department of Mechanical Engineering, Kongju National University, Cheonan 31080, Republic of Korea)

  • Haeng Muk Cho

    (Department of Mechanical Engineering, Kongju National University, Cheonan 31080, Republic of Korea)

Abstract

With the increasing global demand for renewable energy, biodiesel has become a promising alternative to fossil fuels with significant environmental benefits. This article systematically reviews the latest advances in predictive modeling techniques for estimating the characteristics of biodiesel and its impact on diesel engine performance. Various methods for predicting the key performance of biodiesel and the performance and emissions of diesel engines have been summarized. According to the categories of parameters, research cases in recent years have been listed and discussed separately. This review provides a comprehensive overview and serves as a reference for future research and development of biodiesel.

Suggested Citation

  • Wenbo Ai & Haeng Muk Cho, 2024. "Predictive Models for Biodiesel Performance and Emission Characteristics in Diesel Engines: A Review," Energies, MDPI, vol. 17(19), pages 1-25, September.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:19:p:4805-:d:1485763
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    References listed on IDEAS

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    Cited by:

    1. Sajad Ebrahimi & Jing Chen & Raj Bridgelall & Joseph Szmerekovsky & Jaideep Motwani, 2025. "Unlocking the Commercialization of SAF Through Integration of Industry 4.0: A Technological Perspective," Sustainability, MDPI, vol. 17(16), pages 1-44, August.
    2. Ramozon Khujamberdiev & Haeng Muk Cho, 2025. "Hybrid Fuels for CI Engines with Biofuel Hydrogen Ammonia and Synthetic Fuel Blends," Energies, MDPI, vol. 18(11), pages 1-18, May.
    3. Fangyuan Zheng & Haeng Muk Cho, 2024. "Exploring the Effects of Synergistic Combustion of Alcohols and Biodiesel on Combustion Performance and Emissions of Diesel Engines: A Review," Energies, MDPI, vol. 17(24), pages 1-23, December.

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