The effects of nanosecond discharge on ignition characteristics of a stoichiometric methane–air mixture without inert diluent gas were studied by numerical simulation at 0.1 MPa and an initial temperature of 1300 K. ...The effects of nanosecond discharge on ignition characteristics of a stoichiometric methane–air mixture without inert diluent gas were studied by numerical simulation at 0.1 MPa and an initial temperature of 1300 K. A modified non-equilibrium plasma kinetic model was developed to simulate the temporal evolution of particles produced during nanosecond discharge and its afterglow. As important roles in ignition, path fluxes of O and H radicals were analyzed in detail. Different strength of E/N and different discharge duration were applied to the discharge process in this study. And the results presented that a deposited energy of 1–30 m J·cm^(-3) could dramatically reduce the ignition delay time. Furthermore, temperature and radicals analysis was conducted to investigate the effect of non-equilibrium plasma on production of intermediate radicals. Finally, sensitivity analysis was employed to have further understanding on ignition chemistries of the mixture under nanosecond discharge.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
基金Supported by the National Natural Science Foundation of China(No.51376021)the Fundamental Research Funds for the Central Universities(No.2015YJS146)
文摘The effects of nanosecond discharge on ignition characteristics of a stoichiometric methane–air mixture without inert diluent gas were studied by numerical simulation at 0.1 MPa and an initial temperature of 1300 K. A modified non-equilibrium plasma kinetic model was developed to simulate the temporal evolution of particles produced during nanosecond discharge and its afterglow. As important roles in ignition, path fluxes of O and H radicals were analyzed in detail. Different strength of E/N and different discharge duration were applied to the discharge process in this study. And the results presented that a deposited energy of 1–30 m J·cm^(-3) could dramatically reduce the ignition delay time. Furthermore, temperature and radicals analysis was conducted to investigate the effect of non-equilibrium plasma on production of intermediate radicals. Finally, sensitivity analysis was employed to have further understanding on ignition chemistries of the mixture under nanosecond discharge.
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.
