Optimisation of engine performance and emissions fueled by biodiesel blends

Abstract

This study sought to find out the optimisation of engine performance and emissions fueled by biodiesel blends. Compression ignition(CI) engines are most widely used as a power source for many applications, such as automotive and agricultural purposes, as well as portable machines, because of their higher torque, power output, energy content per unit mass, and fuel cost. Unfortunately, CI engines use diesel fuel, which emits greenhouse gases (GHG) and pollutes the environment. Biodiesel has been the preferred alternative fuel due to its benefits of reducing GHG emissions and being used on engines with little or no modification. Biodiesel blends with diesel were introduced to mitigate its decreased engine performance. Unfortunately, it has been difficult to obtain the best blend mix ratios for optimal engine performance and emission since biodiesels are sourced from a variety of vegetable oils whose fuel properties and their interactions differ considerably, causing variation in their combustion processes. The study used non-dominated sorting genetic algorithm II (NSGA II) optimisation to establish the best biodiesel blend to optimise engine performance and emissions. In conclusion, the study found that specific biodiesel blends for various feedstocks (waste vegetable oil, canola, oleander, coconut, and sunflower) achieved the optimal balance between reducing harmful emissions and maintaining engine performance. This study suggests expanding the model's inputs to encompass more fuel properties, engine types, and real-world conditions to improve its applicability, efficiency, and reliability.