Biomass has promising potential as feed material for gasification and subsequent power generation, whereas these sources are seasonal and scattered in the country. Therefore, the consistency of feed material availability and supply chain may be hard to maintain. Gasification with multiple feedstocks, such as biomass-coal-briquette blends, could be one of the practical solutions to mitigate the availability and supply chain problems. Therefore, the present study aims to experiment on an air-downdraft gasifier and use generated producer gas (PG) (, a mixture of gases such as hydrogen, carbon monoxide, carbon dioxide, and nitrogen produced by incomplete combustion of coal/biomass) for power generation through a dual-fuelled mode CI engine. The three input operating conditions for the gasification-engine experiment were GER (0.1–0.43), engine load (0–100%), and compression ratio (CR) 16–18, with output parameters such as engine brake power (BP), brake thermal efficiency (BTE), brake specific energy consumption (BSEC), gas substitution rate (GSR), engine emission (CO, CO2, HC, NOx), and sound. Further optimization using Response Surface Methodology (RSM) was used to obtain the optimal operating conditions with the goal of maximizing engine performance while minimizing emissions. Based on 48 experimental data sets, ANOVA analysis and RSM-based optimization has been conducted. RSM optimization showed the optimum operational conditions of 0.43 GER, 16 CR, and 100% engine load. The respective performance responses were BP 3.52 kW, BSEC 34.16 MJ/kWh, BTE 21.02%, sound intensity 90.21 db, CO 0.0918% vol., HC 17.41 ppm vol., CO2 2.05 %vol., and NOx 4.55 ppm. The average values obtained for R2 were 95–99% and a 0.72 coefficient of determination. Further, the developed model predicted the output response very closely with the experiment, found to be a 4.4% maximum error. Thus, gasification with triple feed material (biomass-coal-briquette) with engine integration could partially substitute diesel fuel with optimum exhaust emission and noise.
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