Explainable AI-assisted sustainable performance optimization of Nano-enhanced rapeseed oil blends in ci engines for optimized engine operation

This study investigates the influence of advanced fuel injection timing on the performance, combustion, and emission characteristics of a compression ignition engine fueled with a rapeseed oil emulsion–pentanol blend (70D25GS5P) supplemented with 150 ppm TiO₂ nanoparticles. Experiments were conducted at injection timings of 21°, 23°, 25°, and 27° crank angle before top dead centre (CA bTDC). Among the tested conditions, 27° CA bTDC produced the highest brake thermal efficiency of 35% and the lowest brake-specific fuel consumption of 0.26 kg kWh⁻1. The corresponding peak cylinder pressure and heat release rate reached 80 bar and 50 kJ deg⁻1 CA, respectively. The lowest hydrocarbon and carbon monoxide emissions, 45 ppm and 0.07%, respectively, were obtained at 23° CA bTDC, whereas 21° CA bTDC resulted in the minimum NOx emission of 2000 ppm. To achieve an improved balance between engine efficiency and emissions, response surface methodology, analysis of variance, desirability-based optimization, and machine-learning approaches were integrated with the experimental analysis. ANOVA demonstrated the significant influence of injection timing on engine performance and emission responses. Among the evaluated machine-learning models, the Gradient Boosting Regressor showed excellent predictive capability, achieving R2 values of 0.999 for brake thermal efficiency and 0.996 for brake-specific fuel consumption. SHAP and Sobol sensitivity analyses further identified engine load as the most influential parameter governing overall engine behaviour, while injection timing exerted a dominant influence on NOx formation. The findings demonstrate that coordinated optimization of engine load and injection timing can improve the performance–emission trade-off of TiO₂-enhanced rapeseed oil emulsion–pentanol fuels, supporting more energy-efficient and sustainable compression ignition engine operation in alignment with Sustainable Development Goal 7.