Thermodynamic performance and emission prediction of CI engine fueled with diesel and Vachellia nilotica (Babul) biomass-based producer gas and optimization using RSM

Abstract

Currently, the requirement of alternate fuel has become significant for the mitigation of petroleum fuel and to reduce exhaust emission. To effectively use alternate fuel with diesel, the present investigation presents a simulation-based prediction of engine performance and emission of a CI engine fueled by Diesel and producer gas derived from Vachellia nilotica (Babul) biomass, and optimization by response surface methodology (RSM). The peculiarity of this study is that it focuses on optimizing the operational parameters of diesel engines that run on babul-based PG combined with diesel fuel to achieve optimal performance and emissions. The data to be used for RSM optimization were obtained by using comprehensive thermodynamic quasi-dimension combustion modeling at different blending ratios (BR), Compression ratio (CR), and Injection timing (IT). Simulation result validation with experimental one was attained with a good agreement. The RSM-based optimization has been employed to optimize the input variables to obtain the best response of dual fueled engine performance (BP, ITE, BSFC) and emission (CO, NO). The RSM study showed that the optimal values of BP, ITE, BSFC, CO, and NO are equals to 3.72 kW, 36%, 0.37 kg/kWh, 0.0091 (vol%), and 245.68 ppm respectively corresponding to BR 65%, CR 18.19, and IT 31.11 bTDC. To check model capability, the regression coefficient obtained was 0.80. According to the ANOVA-based regression modeling, it was found that the results lie lower prediction error R² values for BP, ITE, BSFC, CO, and NO are 96.66%, 97.37%, 97.85%, 97.67%, and 99.79% respectively Thus, RSM is one of the effective tool to predict optimized inputs with the best response of engine performance.

Keywords:

• CI engine modeling
• engine performance
• exhaust emission
• producer gas
• response surface methodology
• optimization

Acknowledgments

We would like to acknowledge the IC engine lab and anonymous reviewers of this manuscript for enhancing the quality of the present manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors

Data availability statement

The authors confirm that the data supporting the findings of this study are available within the article and its supplementary materials.

Table 1. Data for simulation.