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Machine learning predictions for enhancing engine performance and emission using aluminum oxide nano additives in
Murugu Nachippan1, P Pathmanabhan1, Beemkumar Nagappan2
1Department of Automobile Engineering, Easwari Engineering College, Chennai, Tamilnadu, India.
Scientific Reports
|October 21, 2025
Summary
Adding aluminum oxide nanoparticles to castor biodiesel blends improves engine performance and reduces harmful emissions like carbon monoxide (CO), hydrocarbons (HC), and nitrogen oxides (NOx). This sustainable approach enhances fuel economy and combustion efficiency.
Area of Science:
- Green Chemistry and Sustainable Energy
- Nanotechnology Applications in Fuels
- Combustion Engineering
Background:
- Growing concerns over fossil fuel depletion and emissions drive the need for cleaner alternative fuels.
- Biodiesel from non-edible sources like castor oil offers a sustainable option, but requires performance enhancements.
- Improving combustion efficiency and reducing emissions are key for widespread biodiesel adoption.
Purpose of the Study:
- To investigate the impact of aluminum oxide nano-additives on a B30 castor biodiesel blend in compression ignition engines.
- To enhance combustion properties, reduce ignition delay, and mitigate emissions (CO, HC, NOx).
- To apply machine learning for optimizing engine parameters and emissions reduction.
Main Methods:
- Synthesis of biodiesel from castor oil via transesterification.
- Incorporation of aluminum oxide nanoparticles into a B30 biodiesel blend.
- Engine performance testing on a Kirloskar diesel engine under varying loads.
- Application of machine learning algorithms (Random Forest, XGBoost) for data analysis.
Main Results:
- Nano-additive infused biodiesel showed improved fuel economy, atomization, vaporization, and combustion efficiency compared to conventional diesel.
- Reduced brake-specific fuel consumption (BSFC) and significant mitigation of CO, HC, and NOx emissions observed.
- XGBoost algorithm identified as the most accurate predictive tool for engine optimization.
Conclusions:
- Aluminum oxide nano-additives effectively enhance the performance of castor biodiesel blends.
- This integration aligns with green chemistry principles, offering a sustainable energy solution.
- Advanced data analytics, including machine learning, can optimize engine performance and minimize environmental impact.
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