The experimental tests were carried out on a single cylinder hydrogen fueled spark ignition(SI)generator set with different spark timings(4-20℃A bTDC),exhaust gas recirculation(EGR)up to 28% by volume and water injec...The experimental tests were carried out on a single cylinder hydrogen fueled spark ignition(SI)generator set with different spark timings(4-20℃A bTDC),exhaust gas recirculation(EGR)up to 28% by volume and water injection up to 1.95 kg/h(maximum water to fuel mass ratio of 8:1).The engine speed was kept constant of 3000 r/min.The NOx emission and thermal efficiency of engine with gasoline and hydrogen fuel operation at 1.4 kW power output are 5 g/kWh and 12.1 g/kWh,and 15% and 20.9% respectively.In order to reduce the NOx emission at source level,retarding spark timing,exhaust gas recirculation(EGR),and water injection techniques were studied.Nox emission decreased with spark timing retardation,EGR,and water injection.NOx emission with hydrogen at 1.4 kW power output decreased from 12.1 g/kWh with maximum brake torque(MBT)spark timing(10℃A bTDC)to 8.1 g/kWh with retarded spark timing(4℃A bTDC)due to decrease in the in-cylinder peak pressure and temperature.The Nox emission decreased to 6.1 g/kWh with 20% EGR due to thermal and chemical dilution effect.However,thermal efficiency decreased about 33% and 17% with spark timing retardation and 20EGR respectively as compared to that of MBT spark timing.But,in the case of water injection,the NOx emission decreased significantly without affecting the thermal efficiency of the engine and it is 5.6 g/kWh with water-hydrogen ratio of 4:1(water flow rate of 0.92 kg/h).Water injection is the best suitable method to reduce the NOx emission in a hydrogen fueled engine compared with the spark timing retardation and EGR technique.展开更多
The increasing demands on safety, emission and fuel consumption require more accurate control models of micro internal combustion swing engine （MICSE）. The objective of this paper is to investigate the constant spee...The increasing demands on safety, emission and fuel consumption require more accurate control models of micro internal combustion swing engine （MICSE）. The objective of this paper is to investigate the constant speed control models of four-stroke MICSE The operation principle of the four-stroke MICSE is presented based on the description of MICSE prototype. A two-level Petri net based hybrid mode/ is proposed to mode/ the four-stroke MICSE engine cycle. The Petri net subsystem at the upper level controls and synchronizes the four Petri net subsystems at the lower level. The continuous sub-models, including breathing dynamics of intake manifold, thermodynamics of the chamber and dynamics of the torque generation, are investigated and integrated with the discrete model in MATLAB Simulink. Through the comparison of experimental data and simulated DC voltage output, it is demonstrated that the hybrid model is valid for the four-stroke MICSE system. A nonlinear model is obtained from the cycle average data via the regression method, and it is linearized around a given nominal equilibrium point for the controller design. The feedback controller of the spark timing and valve duration timing is designed with a sequential loop closing design approach. The simulation of the sequential loop closure control design applied to the hybrid model is implemented in MATLAB. The simulation results show that the system is able to reach its desired operating point within 0.2 s, and the designed controller shows good MICSE engine performance with a constant speed. This paper presents the constant speed control models of four-stroke MICSE and carries out the simulation tests, the models and the simulation results can be used for further study on the precision control of four-stroke MICSE.展开更多
Volumetric efficiency and air charge estimation is one of the most demanding tasks in control of today's internal combustion engines.Specifically,using three-way catalytic converter involves strict control of the ...Volumetric efficiency and air charge estimation is one of the most demanding tasks in control of today's internal combustion engines.Specifically,using three-way catalytic converter involves strict control of the air/fuel ratio around the stoichiometric point and hence requires an accurate model for air charge estimation.However,high degrees of complexity and nonlinearity of the gas flow in the internal combustion engine make air charge estimation a challenging task.This is more obvious in engines with variable valve timing systems in which gas flow is more complex and depends on more functional variables.This results in models that are either quite empirical(such as look-up tables),not having interpretability and extrapolation capability,or physically based models which are not appropriate for onboard applications.Solving these problems,a novel semi-empirical model was proposed in this work which only needed engine speed,load,and valves timings for volumetric efficiency prediction.The accuracy and generalizability of the model is shown by its test on numerical and experimental data from three distinct engines.Normalized test errors are 0.0316,0.0152 and 0.24 for the three engines,respectively.Also the performance and complexity of the model were compared with neural networks as typical black box models.While the complexity of the model is less than half of the complexity of neural networks,and its computational cost is approximately 0.12 of that of neural networks and its prediction capability in the considered case studies is usually more.These results show the superiority of the proposed model over conventional black box models such as neural networks in terms of accuracy,generalizability and computational cost.展开更多
文摘The experimental tests were carried out on a single cylinder hydrogen fueled spark ignition(SI)generator set with different spark timings(4-20℃A bTDC),exhaust gas recirculation(EGR)up to 28% by volume and water injection up to 1.95 kg/h(maximum water to fuel mass ratio of 8:1).The engine speed was kept constant of 3000 r/min.The NOx emission and thermal efficiency of engine with gasoline and hydrogen fuel operation at 1.4 kW power output are 5 g/kWh and 12.1 g/kWh,and 15% and 20.9% respectively.In order to reduce the NOx emission at source level,retarding spark timing,exhaust gas recirculation(EGR),and water injection techniques were studied.Nox emission decreased with spark timing retardation,EGR,and water injection.NOx emission with hydrogen at 1.4 kW power output decreased from 12.1 g/kWh with maximum brake torque(MBT)spark timing(10℃A bTDC)to 8.1 g/kWh with retarded spark timing(4℃A bTDC)due to decrease in the in-cylinder peak pressure and temperature.The Nox emission decreased to 6.1 g/kWh with 20% EGR due to thermal and chemical dilution effect.However,thermal efficiency decreased about 33% and 17% with spark timing retardation and 20EGR respectively as compared to that of MBT spark timing.But,in the case of water injection,the NOx emission decreased significantly without affecting the thermal efficiency of the engine and it is 5.6 g/kWh with water-hydrogen ratio of 4:1(water flow rate of 0.92 kg/h).Water injection is the best suitable method to reduce the NOx emission in a hydrogen fueled engine compared with the spark timing retardation and EGR technique.
基金Supported by National Natural Science Foundation of China(Grant No.51475422)Science Fund for Creative Research Groups of National Natural Science Foundation of China(Grant No.51221004)
文摘The increasing demands on safety, emission and fuel consumption require more accurate control models of micro internal combustion swing engine （MICSE）. The objective of this paper is to investigate the constant speed control models of four-stroke MICSE The operation principle of the four-stroke MICSE is presented based on the description of MICSE prototype. A two-level Petri net based hybrid mode/ is proposed to mode/ the four-stroke MICSE engine cycle. The Petri net subsystem at the upper level controls and synchronizes the four Petri net subsystems at the lower level. The continuous sub-models, including breathing dynamics of intake manifold, thermodynamics of the chamber and dynamics of the torque generation, are investigated and integrated with the discrete model in MATLAB Simulink. Through the comparison of experimental data and simulated DC voltage output, it is demonstrated that the hybrid model is valid for the four-stroke MICSE system. A nonlinear model is obtained from the cycle average data via the regression method, and it is linearized around a given nominal equilibrium point for the controller design. The feedback controller of the spark timing and valve duration timing is designed with a sequential loop closing design approach. The simulation of the sequential loop closure control design applied to the hybrid model is implemented in MATLAB. The simulation results show that the system is able to reach its desired operating point within 0.2 s, and the designed controller shows good MICSE engine performance with a constant speed. This paper presents the constant speed control models of four-stroke MICSE and carries out the simulation tests, the models and the simulation results can be used for further study on the precision control of four-stroke MICSE.
文摘Volumetric efficiency and air charge estimation is one of the most demanding tasks in control of today's internal combustion engines.Specifically,using three-way catalytic converter involves strict control of the air/fuel ratio around the stoichiometric point and hence requires an accurate model for air charge estimation.However,high degrees of complexity and nonlinearity of the gas flow in the internal combustion engine make air charge estimation a challenging task.This is more obvious in engines with variable valve timing systems in which gas flow is more complex and depends on more functional variables.This results in models that are either quite empirical(such as look-up tables),not having interpretability and extrapolation capability,or physically based models which are not appropriate for onboard applications.Solving these problems,a novel semi-empirical model was proposed in this work which only needed engine speed,load,and valves timings for volumetric efficiency prediction.The accuracy and generalizability of the model is shown by its test on numerical and experimental data from three distinct engines.Normalized test errors are 0.0316,0.0152 and 0.24 for the three engines,respectively.Also the performance and complexity of the model were compared with neural networks as typical black box models.While the complexity of the model is less than half of the complexity of neural networks,and its computational cost is approximately 0.12 of that of neural networks and its prediction capability in the considered case studies is usually more.These results show the superiority of the proposed model over conventional black box models such as neural networks in terms of accuracy,generalizability and computational cost.
