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<p>The present study investigates the impact of soybean oil-based biodiesel–diesel blends (containing 10%, 20%, and 30% biodiesel by volume) on the performance of a single-cylinder diesel engine. To provide a comprehensive analysis, an integrated approach combining experimental testing and numerical simulation was employed. The numerical work was conducted using GT-Power software, utilizing the Woschni heat transfer model and the Wiebe combustion function, which were calibrated against experimental data to predict engine behavior under varying compression ratios and speeds. Furthermore, three types of nano-additives (CNTs, Al<sub>2</sub>O<sub>3</sub>, and Fe<sub>2</sub>O<sub>3</sub>) were incorporated. The results of the numerical model showed a strong correlation with experimental findings, with a maximum error of 9.28% for BSFC and 6.52% for torque, validating the model’s ability to predict performance and combustion characteristics. Numerical results further revealed that nanoparticles shift the combustion phasing closer to Top Dead Center (TDC), enhancing thermal efficiency. Among the additives, CNTs demonstrated notable improvements in reducing BSFC and increasing thermal efficiency, while Fe₂O₃ nanoparticles consistently contributed to enhancements in brake torque and efficiency. These findings underscore the potential of nanoparticle additives to mitigate the adverse performance effects associated with biodiesel usage, offering a promising pathway toward more efficient and sustainable diesel engine operation.</p>

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Experimental Study and Modeling of Diesel Engine Performance with Biodiesel-based Nanofuels from Soybean Oil

  • 期刊论文

  • 发表日期：

    2026年5月16日

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  • Ali Hossein Ghanbari Alouni,
  • Alireza Alipoor,
  • Amir Hajali Kohpayeh

摘要

The present study investigates the impact of soybean oil-based biodiesel–diesel blends (containing 10%, 20%, and 30% biodiesel by volume) on the performance of a single-cylinder diesel engine. To provide a comprehensive analysis, an integrated approach combining experimental testing and numerical simulation was employed. The numerical work was conducted using GT-Power software, utilizing the Woschni heat transfer model and the Wiebe combustion function, which were calibrated against experimental data to predict engine behavior under varying compression ratios and speeds. Furthermore, three types of nano-additives (CNTs, Al2O3, and Fe2O3) were incorporated. The results of the numerical model showed a strong correlation with experimental findings, with a maximum error of 9.28% for BSFC and 6.52% for torque, validating the model’s ability to predict performance and combustion characteristics. Numerical results further revealed that nanoparticles shift the combustion phasing closer to Top Dead Center (TDC), enhancing thermal efficiency. Among the additives, CNTs demonstrated notable improvements in reducing BSFC and increasing thermal efficiency, while Fe₂O₃ nanoparticles consistently contributed to enhancements in brake torque and efficiency. These findings underscore the potential of nanoparticle additives to mitigate the adverse performance effects associated with biodiesel usage, offering a promising pathway toward more efficient and sustainable diesel engine operation.