Multi-objective RSM-based optimization of diesel-diethyl ether blends in diesel engine to achieve sustainable development goals

With the plummeting reserves of fossil fuels at present, there has been a growing imperative for sustainable energy technologies over the last couple of decades. This imperative highlight the need for a shift towards renewable sources, not just to fulfill the current energy demands but also to lessen environmental degradation, fostering an eco-conscious and sustainable future. One way to accomplish such a goal is the utilization of diesel-diethyl ether (D-DEE) blends, instead of neat diesel in compression ignition (CI) engines. This study presents the multi-objective RSM-based analysis and optimization of D-DEE blends (0,5 and 10 %. vol) at manifold engine speeds (1200, 1400, and 1600 rpm). The responses that were recorded in this research included brake power (B.P), brake thermal efficiency (BTE), brake-specific fuel consumption, and CO2 emissions. The results demonstrated an increment in brake power as well as brake thermal efficiency, along with the enhanced CO2 emissions whereas the BSFC decreased while using the Di-ethyl ether enrichment in a 4-stroke CI engine. Upon implementing optimization parameters, the results illustrated the optimal blend ratio of 9.5786 %. vol at 1600 rpm, along with the associated values of B.P, BTE, BSFC, and CO2 emissions which were, 1.26726 kW, 20.861 %, 0.3354, and 7.837 % vol., respectively for this optimized fuel. This study addresses the lack of research on optimizing engine conditions for diesel-DEE blends in CI engines, specifically focusing on diethyl ether as a renewable fuel. Using response surface methodology (RSM), it aims to bridge this gap and contribute to the understanding of optimal blend utilization. The current research also aligns with the attainment of an important sustainable development goal (SDG) which includes the availability of responsible consumption (SDG 12) and improved power generation, contributing towards a greener and cleaner future.