Achieving simultaneous reduction of NOx,CO and unburned hydrocarbon(UHC) emissions without compromising engine performance at part loads is the current focus of dual fuel engine research.The present work focuses on an...Achieving simultaneous reduction of NOx,CO and unburned hydrocarbon(UHC) emissions without compromising engine performance at part loads is the current focus of dual fuel engine research.The present work focuses on an experimental investigation conducted on a dual fuel(diesel-natural gas) engine to examine the simultaneous effect of inlet air pre-heating and exhaust gas recirculation(EGR) ratio on performance and emission characteristics at part loads.The use of EGR at high levels seems to be unable to improve the engine performance at part loads.However,it is shown that EGR combined with pre-heating of inlet air can slightly increase thermal efficiency,resulting in reduced levels of both unburned hydrocarbon and NOx emissions.CO and UHC emissions are reduced by 24% and 31%,respectively,The NOx emissions decrease by 21% because of the lower combustion temperature due to the much inert gas brought by EGR and decreased oxygen concentration in the cylinder.展开更多
Great efforts have been made to resolve the serious environmental pollution and inevitable declining of energy resources. A review of Chinese fuel reserves and engine technology showed that compressed natural gas (CN...Great efforts have been made to resolve the serious environmental pollution and inevitable declining of energy resources. A review of Chinese fuel reserves and engine technology showed that compressed natural gas (CNG)/diesel dual fuel engine (DFE) was one of the best solutions for the above problems at present. In order to study and improve the emission performance of CNG/diesel DFE, an emission model for DFE based on radial basis function (RBF) neural network was developed which was a black-box input-output training data model not require priori knowledge. The RBF centers and the connected weights could be selected automatically according to the distribution of the training data in input-output space and the given approximating error. Studies showed that the predicted results accorded well with the experimental data over a large range of operating conditions from low load to high load. The developed emissions model based on the RBF neural network could be used to successfully predict and optimize the emissions performance of DFE. And the effect of the DFE main performance parameters, such as rotation speed, load, pilot quantity and injection timing, were also predicted by means of this model. In resumé, an emission prediction model for CNG/diesel DFE based on RBF neural network was built for analyzing the effect of the main performance parameters on the CO, NOx emissions of DFE. The predicted results agreed quite well with the traditional emissions model, which indicated that the model had certain application value, although it still has some limitations, because of its high dependence on the quantity of the experimental sample data.展开更多
Cape Chestnut oil was processed to biodiesel through transesterification. Cape Chestnut kennels are reported to have oil content of 60% - 63% [1]. Properties of biodiesel were determined and compared with those of die...Cape Chestnut oil was processed to biodiesel through transesterification. Cape Chestnut kennels are reported to have oil content of 60% - 63% [1]. Properties of biodiesel were determined and compared with those of diesel and engine tests done at a constant speed of 1500 RPM on the biodiesel blends to evaluate their performance and emissions characteristics. Performance evaluation was in terms of Brake Specific Fuel Consumption (BSFC), Brake Horse Power (BHP) and Brake Thermal Efficiency (ETE). The engine was initially run on diesel to establish the reference characteristics before running on biodiesel blends. The biodiesel was blended with diesel volumetrically to 80% (B80), 50% (B50), 20% (B20) and 5% (B5) the percentage being the volume of biodiesel in the blended fuel. Diesel fuel had the lowest BSFC followed by B5 whose BSFC was 7.3% higher than that of diesel. BTE for B100 was lower than that of diesel by 20.3% while that of B5 was 7.6% lower. Concentration of SO2 in B100 was 92.7% lower than that of diesel fuel while that of B20 was 24.7% lower. NO and NO2 concentrations for B100 were around 15% higher than that of diesel. Particulate matter of less than 10 μm diameter (PM10) for diesel was found to be 72% of the total collected from all the test fuels as compared to that of biodiesel blends at 28%. The study concluded that Cape Chestnut biodiesel blends containing up to 20% biodiesel can be used in an unmodified diesel engine since their performance and emission characteristics were very similar to that of diesel but with reduced toxic gas emissions therefore friendly to the environment.展开更多
文摘Achieving simultaneous reduction of NOx,CO and unburned hydrocarbon(UHC) emissions without compromising engine performance at part loads is the current focus of dual fuel engine research.The present work focuses on an experimental investigation conducted on a dual fuel(diesel-natural gas) engine to examine the simultaneous effect of inlet air pre-heating and exhaust gas recirculation(EGR) ratio on performance and emission characteristics at part loads.The use of EGR at high levels seems to be unable to improve the engine performance at part loads.However,it is shown that EGR combined with pre-heating of inlet air can slightly increase thermal efficiency,resulting in reduced levels of both unburned hydrocarbon and NOx emissions.CO and UHC emissions are reduced by 24% and 31%,respectively,The NOx emissions decrease by 21% because of the lower combustion temperature due to the much inert gas brought by EGR and decreased oxygen concentration in the cylinder.
文摘Great efforts have been made to resolve the serious environmental pollution and inevitable declining of energy resources. A review of Chinese fuel reserves and engine technology showed that compressed natural gas (CNG)/diesel dual fuel engine (DFE) was one of the best solutions for the above problems at present. In order to study and improve the emission performance of CNG/diesel DFE, an emission model for DFE based on radial basis function (RBF) neural network was developed which was a black-box input-output training data model not require priori knowledge. The RBF centers and the connected weights could be selected automatically according to the distribution of the training data in input-output space and the given approximating error. Studies showed that the predicted results accorded well with the experimental data over a large range of operating conditions from low load to high load. The developed emissions model based on the RBF neural network could be used to successfully predict and optimize the emissions performance of DFE. And the effect of the DFE main performance parameters, such as rotation speed, load, pilot quantity and injection timing, were also predicted by means of this model. In resumé, an emission prediction model for CNG/diesel DFE based on RBF neural network was built for analyzing the effect of the main performance parameters on the CO, NOx emissions of DFE. The predicted results agreed quite well with the traditional emissions model, which indicated that the model had certain application value, although it still has some limitations, because of its high dependence on the quantity of the experimental sample data.
文摘Cape Chestnut oil was processed to biodiesel through transesterification. Cape Chestnut kennels are reported to have oil content of 60% - 63% [1]. Properties of biodiesel were determined and compared with those of diesel and engine tests done at a constant speed of 1500 RPM on the biodiesel blends to evaluate their performance and emissions characteristics. Performance evaluation was in terms of Brake Specific Fuel Consumption (BSFC), Brake Horse Power (BHP) and Brake Thermal Efficiency (ETE). The engine was initially run on diesel to establish the reference characteristics before running on biodiesel blends. The biodiesel was blended with diesel volumetrically to 80% (B80), 50% (B50), 20% (B20) and 5% (B5) the percentage being the volume of biodiesel in the blended fuel. Diesel fuel had the lowest BSFC followed by B5 whose BSFC was 7.3% higher than that of diesel. BTE for B100 was lower than that of diesel by 20.3% while that of B5 was 7.6% lower. Concentration of SO2 in B100 was 92.7% lower than that of diesel fuel while that of B20 was 24.7% lower. NO and NO2 concentrations for B100 were around 15% higher than that of diesel. Particulate matter of less than 10 μm diameter (PM10) for diesel was found to be 72% of the total collected from all the test fuels as compared to that of biodiesel blends at 28%. The study concluded that Cape Chestnut biodiesel blends containing up to 20% biodiesel can be used in an unmodified diesel engine since their performance and emission characteristics were very similar to that of diesel but with reduced toxic gas emissions therefore friendly to the environment.
