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Biomass is one of the attractive alternative fuels, which exists dispersively. Small size gas engine power generation with gasification biomass gas is one of the efficient methods. However, since its calorific value is lower and its composition can be affected by gasifying conditions, it is difficult to stabilize and achieve high thermal efficiency engine operation. This study aims to develop a small size gas engine system with biomass gas by modifying the control system of a conventional spark ignition engine. In this paper, effect of fuel composition on combustion was clarified experimentally to get guideline for the engine control system.

In this paper, an online automatic adaptation method for model-based control of a diesel engine is developed. Control-oriented models based on physics has been proposed as substitutes for conventional control methods to improve the performance of engine under real driving situation. Even such physical-rich models have fitting parameters and it is preferable to adapt the parameters according to the real-time operating condition. Therefore, an automatic adaptation method for the model is developed, and the method is based on neural network. The prediction accuracy of the model is evaluated by simulation and it is confirmed that the method can be applied online to a real engine by experiment.

Autoignition and combustion characteristics of biomass gas were investigated experimentally. A mock biomass gas consisting of H2, CH4, CO, N2 and CO2 was used as a wood pyrolysis gas. Experiments were carried out with a modified gas engine varying equivalence ratio and fuel composition. High hydrogen content increases the combustion speed, but it hardly affects ignition timing. Carbon monoxide in fuels does not affect combustion speed largely. The autoignition temperature of biomass gas is about 1000K, which is the same as those of hydrocarbon fuels. The engine also realizes 42% of the indicated thermal efficiency and a maximum IMEP of 0.3MPa.