Intelligent Decision-Based Hydrogen-Biodiesel engine to improve engine performance

Abstract

This study highlights the urgent need to improve the performance of biodiesel engines in light of the growing environmental challenges that are mostly brought on by a rise in vehicle usage. It introduces a novel approach by combining vegetable oil and hydrogen as an alternative fuel and using a Decision Elman Neural Framework (DENF) to adjust engine settings. Through the implementation of an all-inclusive strategy that includes data gathering, pre-processing, feature analysis, and real-time tracking, the system aims to increase engine performance while reducing environmental impact. A comparison with traditional techniques highlights the improved engine performance and reduced emissions that the suggested method achieves. Combining vegetable oil and hydrogen with DENF appears to be a key tactic for increasing engine efficiency and promoting sustainability in biodiesel engines. The data-driven approach results in a significant 7.4% improvement in engine performance and a 2.1% decrease in peak emissions. On the other hand, it is linked to a 19.8% increase in CO emissions and a 5.6% decrease in soot emissions, indicating better engine performance and a sustainable environment.