Research and optimization of hydrogen addition and EGR on the combustion, performance, and emission of the biodiesel-hydrogen dual-fuel engine with different loads based on the RSM.

Pollutants produced by engines are a significant source of environmental pollution, so the study of engine emissions is very important. In this study, with CONVERGE software, a diesel engine model of the engine was produced. To better obtain the characteristic results of the engine, this was coupled with an improved chemical kinetics mechanism. Then, the results of this model were verified experimentally. Additionally, the effects of four different EGR rates on the combustion, performance, and emissions of a dual-fuel diesel engine were investigated by the verified model under different (50 %, 75 %, and 100 %) load conditions. Lastly, the brake specific fuel consumption, NOx emission, and HC emission were optimized by the response surface methodology (RSM). The results show that the pressure, temperature, and NOx emission in the engine's cylinder can all be reduced by raising the EGR at three different loads. Besides, the optimization results show that the engine achieves the best operating conditions at 100 % load, hydrogen fraction of 6.92 %, and EGR rate of 7.68 %.

Effect of Different Ratios of Gasoline-Ethanol Blend Fuels on Combustion Enhancement and Emission Reduction in Electronic Fuel Injection Engine.

The severity of engine emissions for the environment and human health cannot be ignored. This article optimizes the combustion and emission of gasoline-cassava bioethanol fuel blends in electronic fuel injection engines using response surface methodology to achieve the goal of reducing carbon and pollutant emissions. The experiment investigated the effects of different gasoline-cassava bioethanol mixing ratios (G100, G90E10, G80E20, and G70E30) on engine performance, including torque, brake specific fuel consumption, power, total hydrocarbons, nitrogen oxides, and carbon monoxide emissions. The results show that the gasoline-cassava bioethanol fuel blend is not as good as G100 in terms of braking power, torque, and brake specific fuel consumption, but better than G100 in terms of carbon monoxide emissions and total hydrocarbon emissions. Then, the optimization objective function was determined, and the combustion and emission characteristics were optimized using the response surface methodology method. The optimization results indicate that the response surface methodology method can determine the interaction between design variables such as brake specific fuel consumption, nitrogen oxides, and total hydrocarbon emissions and find the best solution. In this experiment, the independent variables of the best solution were 72.9 N·m torque, 30% G70E30 mixing rate, and 2000 rpm speed, corresponding to brake specific fuel consumption at 313 g/(kW·h), nitrogen oxide emissions at 2.85 × 103 ppm, and total hydrocarbon emissions at 166 ppm. The findings of this study indicate that by optimizing the gasoline-cassava bioethanol mixture ratio, lower emission levels can be achieved in electronic fuel injection engines, thereby promoting the sustainable development of renewable energy and reducing pollutant emissions.