Multi-objective optimization of operating parameters for a H2/Diesel dual-fuel compression-ignition engine. (31st July 2020)

• Record Type: Journal Article
• Authors: Jabbr, Abdulhakim I.; Gaja, Haythem; Koylu, Umit O.
• Is Part Of: International journal of hydrogen energy. Volume 45:Number 38(2020)
• Page Start: 19965
• Page End: 19975
• Publication Date: 2020-07-31
• Subjects: Hydrogen -- Diesel -- Dual-fuel engine -- NOx formation -- Soot formation -- Optimization; Hydrogen as fuel -- Periodicals; Hydrogène (Combustible) -- Périodiques; Hydrogen as fuel; Periodicals; 665.81
• DOI: 10.1016/j.ijhydene.2020.05.071
• Languages: English
• ISSNs: 0360-3199

Abstract

Abstract: This numerical study covers the engine performance and emissions of a dual-fuel compression-ignition engine fueled by hydrogen/diesel mixtures. Advanced simulations of the combustion process were performed by focusing on simulating the engine performance and emissions at different hydrogen quantities. Different factors that have significant effects on engine performance and emissions, such as exhaust gas recirculation and modifying diesel injection timing (IT), were also considered in this study. The relationship between the performance, emissions, and the operating parameters considered in this work are investigated and explained. A significant reduction of soot emissions by approximately 32.5% has been achieved by increasing hydrogen levels up to 37.5%; however, this has led to an increase in nitrogen oxides (NOx) emissions by ~22%. To overcome this problem, the optimum operating parameters that will lead to minimum emissions and maximum efficiency were also sought. Hydrogen rates, exhaust gas recirculation (EGR) rates, and diesel injection timing were the main operating conditions while the engine performance and NOx/soot emissions were the objectives. The best operating conditions for hydrogen/diesel engines were obtained by solving the multi-objective problem of maximizing the efficiency while minimizing the NOx and soot emissions. This multi-objective optimization problem (MOOP) with conflicting objectives was solved by using different optimization techniques, including regression analysis, artificial neural networks, and genetic algorithms. By solving MOOP, the first preferred operating condition at ~13% hydrogen, 4% EGR, and 30 BTDC of diesel injection timing was obtained. Highlights: Performance and emissions of CI dual fuel engine were studied. Increasing hydrogenled to reduction in soot and ignition timing delayed. Increased EGR levels reduced NOx but also reduced power. ANOVA was used to determine the most significant parameters. GA-NN was used to find optimal trade-offs between efficiency, soot and NOx.