Modeling H2-enriched dual fuel engine performance and emissions

Abstract

This study utilizes a validated GT-Power simulation model to evaluate hydrogen (H2) enrichment effects on the performance and emissions of a four-cylinder, 86 kW dual-fuel diesel engine. The primary goal is identifying operating strategies that enhance efficiency while maintaining nitrogen oxide (NOx) emissions at or below baseline levels, termed "NOx neutral" operation. The methodology involves adjusting engine load between 2 and 16 bar brake mean effective pressure (BMEP) and varying H2 energy substitution from 10% to 70% at 1500 rpm. To analyse complex non-linear relationships, this research employed response surface methodology (RSM) and a random forest (RF) machine learning algorithm. Results indicate optimal H2 substitution lies in the 20-30% range, yielding a 2-3% improvement in brake thermal efficiency (BTE) and a significant decrease in brake specific fuel consumption (BSFC) from 200-220 g/kWh to 160-180 g/kWh. While CO2, HC, and CO emissions decreased, NOx remained stable only up to 25% substitution, increasing sharply thereafter. Consequently, H2 energy contribution should be limited to 25% to effectively control NOx. The combined use of simulation with RSM and RF models proves an efficient, accurate method for engine analysis, minimizing extensive physical testing requirements.