Parametric optimization of the CNG/ethanol-induced RCCI profiles in biodiesel combustion through a robust design space foray

To attain a "net-zero carbon footprint," plant-based biodiesel should be used in conventional IC engines with naturalizing other important emission characteristics like nitrogen oxide and carbon footprint. This study uses a statistical modeling-based multi-objective optimization approach to find the compromise parametric solution for the combustion, performance, stability, and emissions of a diesel engine powered by Mahua biodiesel mixed with compressed natural gas (CNG)/ethanol. This current study was conducted through an advanced injection strategy called the split injection approach, followed by various energy shares from ethanol or CNG enrichment through port fuel injection strategies. Hence the engine operation was conducted with the fuel mixture of various reactivity in different proportions. However, the injection angle was counted as an effective input parameter along with the variation in energy share for different injection angles. A robust 'design of experiment' (DoE) approach was incorporated here by a novel strategy developed by Scott Kowalski, John Cornell, and Geoff Vining (KCV) to investigate this multi-factor approach which combines both reactivity phasing and injecting phasing strategies. The Response Surface Methodology (RSM) based statistical modeling was incorporated here to predict the corresponding responses in continuous design space. It is pertinent to mention that the combination of this novel DoE-RSM-based injection and reactivity phasing is a first-of-a-kind in this paradigm as per the current literature. The robust model's best desirable responses showed improved combustion, performance, and emission characteristics while remaining within US Environmental Protection Agency (EPA) limits. The NHC & CO footprint of the best optimal strategy was almost 15% and 60% lower for ethanol enriched biodiesel operation and 50% & 80% lower for PFI-CNG operation, respectively, the experimental values corresponding to the highest LNVIMEP & lowest COVIMEP. PM footprint has also illustrated an almost 40% lower footprint corresponding to the lowest ROPRMAX for ethanol enriched strategy and 5% reduced emission for CNG-BD operation corresponding to maximum CD. Improved EQ_BTE and CO2 footprint were registered by almost 6 % & 60% for PFI of ethanol and 20% and 10% for CNG-BD operation, respectively, compared to their experimental values corresponding to the lowest ROPRMax.