Prediction and performance optimisation of a DI CI engine fuelled diesel–Bael biodiesel blends with DMC additive using RSM and ANN: Energy and exergy analysis

Abstract

Synthesis of biofuel from bioresources represents one of the greatest propitious options for achieving a cleaner production of energy and the global circular bio-economy. The superior cetane rating of biodiesel makes it a fitting fuel for CI diesel engines. The present study aims to valorise Bael seeds for biodiesel production. Bael is a species of tree indigenous to India. The diesel-Bael biodiesel was blended with dimethyl carbonate (DMC) as an ignition enhancer and investigated in a selected diesel engine. This work reports that the Bael biodiesel blend gets a tolerable level of BTE against neat fossil diesel. An utmost BTE of 30.68% was achieved with B15DMC5 which is very close to diesel (31.8%) at peak load. Certainly, BSFC was suppressed and emissions lessened by DMC inclusion. For instance, the CO and HC emissions substantially reduced to a minimum of 0.19% and 179 ppm with the B17.5DMC2.5 blend at peak load. NOx emission is directly proportional to Bael biodiesel concentration, Notably, NOx emission is well controlled at 50% and 75% load even though with the increasing biodiesel concentration in the blend. Though, control of emissions at peak load is still a crucial issue. Nevertheless, the DMC additives controlled the NOx emission at peak load. B15DMC5 blend exhibits progress in combustion through the optimized value of HRR, CGP, and CGT against B20. The presence of NOx and smoke opacity without additives is suppressed up to 7% and 10% with additives. Availability (exergy) and exergy efficiency at different loads of both neat diesel and blended fuels, mainly shaft, cooling water, and exhaust availability were calculated. The results of the study illustrated that the input availability increased at peak loads, as well as gross work output, was maximum at peak load due to higher fuel exergy present in the combustion chamber. A maximum exergy efficiency of 68% was recorded by B15DMC5 at peak load. Finally, the process optimization by RSM has been validated by experimental results and further authenticated with ANN. The results of the RSM model promote it as statistically significant. Generate the regression equation for all output responses. The optimized operating parameters of engine load of 50%, 10% of biodiesel blend, and additive concentration of 3.59% achieved the most optimum output response. The results of the predicted optimized condition of BTE, BSFC, CO, HC, NOx, and Smoke opacity showed 24.051%, 0.441861 kg/kW hr, 0.2028%, 113.607 ppm, 316.099 ppm, and 14.4286% respectively. The R2 values from RSM and ANN DoE models were 0.992834 and 0.99984. This study concludes that a superior precision certainty from both RSM and ANN models is beneficial for engine overall performance estimation. This phenomenon provides a good sign to implement the ANN to forecast engine operational behavior in the future. The novel approach of process optimization by RSM and ANN for Bael biodiesel with DMC blended fuel operate DI CI engine supports the SDGs of the UN such as Good health and Well being (SDG: 3), Affordable and Clean Energy (SDG: 7), Responsible Consumption and Production (SDG: 12), Climate Action (SDG: 13) and Life on Land (15).