A complex thermochemical process during biomass gasification includes many chemical reactions. Therefore, a stoichiometric model can be applied to predict the composition of the producer gas during gasification. However, the prediction of methane and hydrogen gas is still limited by a significant margin using the present stoichiometric models. The purpose of this research was to develop novel stoichiometric models that account for the reaction equilibrium constant with correction factors. The new models would enable forecasting of the composition of CO, CO₂, CH₄, H₂, N₂, tar, lower heating value (LHV), and cold gasification efficiency (CGE). Model development consisted of two stages, whereas the development of the models and their validation adopted an artificial neural network (ANN) approach. The first stage was calculating new correction factors and defining the new equilibrium constants. The results were six stoichiometric models (M1–M6) with four sets of correction factors (A–D) that built up the new equilibrium constants. The second stage was validating the models and evaluating their accuracy. Validation was performed by the Root Mean Square Error (RMSE), whereas accuracy was evaluated using a paired t-test. The developed models predicted the composition of the producer gas with an RMSE of less than 3.5% and ΔH-value of less than 0. The models did not only predict the composition of the producer gas, but they also predicted the tar concentration. The maximum tar concentration was predicted by M2C with 98.733 g/Nm³ at O/C 0.644, H/C 1.446, ER 0.331, and T 923 K. The composition of producer gases (CO, CO₂, H₂, and N₂) was accurately predicted by models M1D, M2C, and M3C. This research introduces new models with variables N/C, O/C, H/C, ER, and T to simulate the composition of CO, CO₂, CH₄, H₂, N₂, and LHV-gas, with R² > 0.9354, tar (C₆H₆)-R² of 0.8638, and CGE-R² of 0.8423. This research also introduces correction factors and a new empirical correlation for the reaction equilibrium constants in new stoichiometric models using steam reforming.

Biomass is a potential alternative energy source. This study offers a comprehensive analysis of biomass gasification as an energy source, particularly its application in diesel engines, gas engines, and gas turbines. No specific research has been identified that addresses syngas utilization as fuel for internal combustion engines. The paper employs the PRISMA methodology to select and analyze observations. The examination encompasses four subjects: biomass, reactor gasification, operational parameters, and syngas for internal combustion. The Van Krevelen diagram is employed to analyze the characteristics of biomass that produce high-energy syngas, efficiency, variable calorific value of syngas, and decreased power output. Feedstock, gasification reactors, and operational conditions significantly influence the generation of biomass gasification syngas. A downdraft reactor is appropriate for small- to medium-scale gasification. The utilization of biomass gasification technology and syngas as fuel for internal combustion engines is investigated. The hydrogen-to-carbon ratio (H/C), oxygen-to-carbon ratio (O/C), high temperature, low ash content, low equivalence ratio (ER), and the amount of air in the syngas all affect its calorific value. The advantages of utilizing syngas include reduced pollutants, decreased reliance on diesel fuel, and a reduction in diesel fuel use in internal combustion engines. The disadvantages of syngas include necessary engine modifications, decreased thermal efficiency, the calorific value of syngas, and decreased power generation.

The usage of palm oil empty fruit bunches (EFBs) in the gasification process adds value to the empty bunches as a renewable energy source. In this study, we design and manufacture a new updraft type of gasifier reactor without a blower so that it does not require electric power in its operation, but uses power from engine suction. Our test results compare the use of biomass waste in conjunction with diesel fuel to run a diesel power plant for 20 min at a load of 10,000 W: diesel with coconut shell charcoal (350 mL), diesel with acacia wood charcoal (380 mL), and diesel with EFB charcoal (400 mL). The test shows that the highest efficient and the most optimal biomass in the gasification process is coconut shell charcoal, because coconut shell charcoal has a dense structure and, at the time of the experiment, the coconut shell charcoal was filled 15 cm below the gas outlet pipe hole. From the standpoint of the economic value of the gasifier reactor that is proposed in this study, the result with the lowest cost is that of diesel with EFB charcoal, because, in this experiment, EFBs were the biomass that was not purchased. The additional use of empty fruit bunches of charcoal is able to save 50% diesel usage.