A comparative assessment of ternary blends of three bio-alcohols with waste cooking oil and diesel for optimum emissions and performance in a CI engine using response surface methodology. (15th January 2018) - Krishnamoorthy, V.; Dhanasekaran, R.; Rana, D.; Saravanan, S.; Rajesh Kumar, B.
Graphical abstract: Highlights: Alcohols can reduce viscosity of WCO as a ternary blend with diesel. Three bio-alcohols propanol, butanol and pentanol were used. Optimization of EGR, injection timing and alcohol for optimum emissions & performance. Optimization was performed using desirability approach of the RSM. RSM could model, predict, optimize engine characteristics with reasonable accuracy. Abstract: Recycling waste cooking oil (WCO) for use in diesel engines offers a sustainable solution for ecological wellbeing and energy security. Diesel-WCO-alcohol ternary blends provide a straightforward and cost-effective opportunity to utilise both a bio-component & a recycled component to partially replace diesel and to reduce viscosity of WCO instead of expensive pre-heating and trans-esterification. Three bio-alcohols, n -propanol (Pr), n -butanol (Bu) and n -pentanol (Pe) were chosen for this purpose. An investigation was carried out to compare the effects of adding three bio-alcohols to form ternary blends with WCO and diesel (D) individually (D50-WCO30-Pr20, D50-WCO30-Bu20 and D50-WCO30-Pe20) for optimum engine characteristics by employing a response surface methodology (RSM) based optimization using a 3-factor × 3-level full factorial experimental design. Three alcohols, three injection timings (23°, 25° and 27°CA bTDC) and three EGR rates (10, 20 and 30%) were chosen as factors and their levels. Regression models were developed for NOx, smoke, HC, CO, BTE and BSFC and were found to be statistically significant. Interactive effects between injection timing and EGR for all blends were presented. Pentanol was found to be a suitable alcohol for this purpose as the ternary blend D50-WCO30-Pe20 injected at 23°CA bTDC at 15% EGR had the highest desirability. Confirmatory tests validated that the models developed were adequate and the error in prediction is within 6%.