Enhancing environmental sustainability: ANN-based performance and emissions optimisation of a diesel engine using Al 2 O 3 -enhanced waste cooking oil biodiesel

Abstract The growing demand for cleaner ignition and sustainable energy solutions has accelerated the adoption of biodiesel as an alternative to conventional diesel fuel. But its practical application is constrained by lower calorific value and higher viscosity. This study proposes an integrated approach to improve diesel engine performance and lower emissions by utilising waste cooking oil-based biodiesel incapacitated with aluminium oxide (Al 2 O 3 ) nanoparticles and optimising fuel injection timings (FITs). A comprehensive experimental investigation was conducted at FITs of 19°, 21°, 23°, and 25° before top dead centre (bTDC) on a single cylinder, four-stroke, water-cooled, direct-injection diesel engine at full load conditions. Test fuels included conservative diesel (PD), a 20 % biodiesel blend (WB20DP), and nanoparticle-enhanced blends containing 250, 500, and 1,000 ppm. The results showed that nanoparticles addition significantly enhanced combustion characteristics and engine performance. The WB20PD + 1,000 ppm blend showed the highest brake thermal efficiency (BTE) of 33.9 %, above that of PD (32.7 %) at 25 ° bTDC. Maximum cylinder pressure similarly increased to 94.503 bars compared to 92.446 bars for PD. The improved thermal performance is attributed to enhanced atomisation, oxygen availability, and catalytic effects of nanoparticles, leading to reduced ignition delay and more complete combustion. An artificial neural network (ANN) model effectively captured the complex relationships between engine parameters and performance outcomes, with regression values exceeding 0.95, validating its reliability as a predictive optimisation tool.