Bald eagle search optimization on dual fueled reactivity controlled combustion ignition based engine characteristics by altering low reactive fuels

Abstract

AbstractIn conventional diesel engines, the reactivity controlled combustion ignition (RCCI) systems find to be offer better emission and engine performances. The main aim of this work is to study and enhance the emission, combustion, and performance characteristics of the RCCI based diesel engine. In the present work, we compare and optimize the characteristics of the diesel engines when using methane added hydrogen and methanol fuels as low reactive fuels (LRF). The diesel and dimethyl ether added biodiesel (spirulina microalgae) are used as high reactivity fuels (HRF) with six different proportion rates. In this, initially, the experimental results are investigated by using methanol as LRF with HRF fuel, and better blend proportion is optimized by using bald eagle search optimization (BESO) performed in the Matlab platform. Then, the methane content added hydrogen is used as LRF with the optimized HRF fuel combinations. Finally, from both cases, the optimized experimental characteristics are predicted with the help of the Elman recurrent neural network based BESO. In which, the hydrogen gas contributed RCCI engine provide supreme engine characteristics such as 217.6 g/kWh of specific fuel consumption, 38.7% of brake thermal efficiency, 84.45 bar of cylinder pressure, and the CO2 and NOx emissions are 539.2 g/kWh, and 1020 ppm. The result reveals that the proposed predicted results are superiorly validated the experimental outcomes with minimal errors.