Performance simulation and optimization of SI engine fueled with peach biomass-based producer gas and propane blend

• Published in: Thermal science and engineering progress 2023-06, Vol.41, p.101816, Article 101816
• Main Authors: Raj, Reetu, Kumar Singh, Deepak, Vachan Tirkey, Jeewan
• Format: Article
• Language: English
• Subjects: Engine performance; Exhaust emission; Peach-biomass; Quasi-dimensional combustion model; Response surface methodology
• ISSN: 2451-9049; 2451-9049
• DOI: 10.1016/j.tsep.2023.101816

•Performance analysis of SI engine fuelled with Peach based producer gas and propane blends.•Quasi-dimensional thermodynamic computational model was developed, validated and predicted.•RSM-Optimum inputs found as: 90% blend, 1.002 equivalence ratio, and 33.83 bTDC spark timing.•Optimum performance obtained as: 2.41 kW BP, 0.3003 kg/kWh BSFC, and 27.19 % BTE.•NO emissions decreased as spark timing and propane blend in producer gas decreased. Biomass and agricultural waste can be used to generate electricity in remote areas through a Gasifier-engine-generator set. However, producer gas-fueled engines have low power and thermal efficiency. In this view, the objective of this study is to determine optimum operation setting of a spark ignition (SI) engine with improved efficiency, reduced emissions, and fuel consumption. Hence, in the present study, initially, SI engine performance and emission have been simulated through a comprehensive quasi-dimensional thermodynamic model. Thereafter, parametric optimization has been performed to improve the performance of SI engines fueled with peach-based producer gas (PG) and propane blend. The effect of blending percentage, equivalence ratio, and start of ignition (SOI) timing has been considered to analyze the engine performance using response surface methodology (RSM). The experiments were designed according to the design of experiment (DoE) tool based on RSM and optimized using the desirability approach. The use of ANOVA to form regression models resulted high accuracy in forecasting output response variables with a 95% confidence interval. RSM results depict, optimum input parameters to be 90 blend percentage, 1.002 equivalence ratio (ER), and 33.83 SOI at 1500 rpm. Corresponding to these optimal inputs, response output performances were found to be 2.41 kW, 0.3003 kg/kW-hr, 27.19 %, 0.809 (vol.%), 2026.05 (ppm) for brake power (BP), Brake specific fuel consumption (BSFC), Brake thermal efficiency (BTE), CO, and NO respectively, with a composite desirability of 0.868. Thus, RSM has the potential to optimize the performance and emission characteristics of engines fuelled with propane and PG.