The effect of additive addition to fuel with variations in preheating and water coolant on multi-cylinder diesel engine performance

Authors

  • Faisal Abdul Aziz Universitas Negeri Semarang Author
  • Sonika Maulana Universitas Negeri Semarang Author
  • Rizqi Fitri Naryanto Universitas Negeri Semarang Author
  • Hanif Hidayat Universitas Negeri Semarang Author

DOI:

https://doi.org/10.15294/jmel.v13.i2.5076

Keywords:

Diesel Fuel Conditioner, Dexlite, Engine Performance, Preheating, Water Coolant

Abstract

Diesel engines are essential for transporting heavy loads, requiring significant engine power. This study aims to evaluate the effect of adding PTT (diesel fuel conditioner) additives to Dexlite fuel, focusing on mixtures of D0, D1, and D2. Additionally, variations in fuel pre-heating and engine cooling system fluids are examined. This research employs an experimental approach with descriptive analysis. The findings indicate that the optimal torque occurs with the D2 mixture, achieving 136.57 N·m at 2267 rpm with standard coolant, 152.03 N·m at 2100 rpm with a 50%:50% fluid ratio, and 160.70 N·m at 2033 rpm with a 30%:70% fluid ratio, all without pre-heating. The optimal power values for the D2 mixture are 74.60 HP at 4600 rpm with standard fluid, 75.23 HP at 4100 rpm with a 50%:50% fluid ratio, and 78.03 HP at 4000 rpm with a 30%:70% fluid ratio, also without pre-heating. The average results show that the D1 and D2 mixtures improve torque values by 0.77% and 4.75%, respectively, and enhance power by 0.19% and 1.53% compared to pure Dexlite. In contrast, pre-heating at 50°C, 60°C, and 70°C resulted in a decrease in torque of 1.00%, 2.26%, and 3.62%, respectively, and a reduction in power of 0.56%, 2.29%, and 4.79% compared to normal temperature conditions.

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Published

2025-05-12

Article ID

5076

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Section

Articles

How to Cite

The effect of additive addition to fuel with variations in preheating and water coolant on multi-cylinder diesel engine performance. (2025). JMEL : Journal of Mechanical Engineering Learning, 13(2), 55-61. https://doi.org/10.15294/jmel.v13.i2.5076