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
Earthquake magnitude and rupture duration are among the most important parameters characterizing an earthquake for the purpose of early tsunami warning. While they can be routinely determined from broadband P waveform...Earthquake magnitude and rupture duration are among the most important parameters characterizing an earthquake for the purpose of early tsunami warning. While they can be routinely determined from broadband P waveforms with iterative inver- sion procedures, the inversion procedures may fail when the rupture either lasts longer than the interval between P and later ar- rivals or requires too much time or human intervention. Little contaminated by later arrivals, high frequency P waves are useful for modeling earthquake source processes, though the envelope waveform is affected by strong scattering in lithosphere. With high frequency envelopes from aftershocks as Empirical Green＇s Function （EGF）, the coda effects can be removed and more accurate relative source time function （RSTF） of the main shock can be obtained. Assuming that RSTFs cannot be negative, we use the projected Landweber deconvolution method （PLD） to obtain high frequency RSTFs because PLD method has the ad- vantage of non-negativity, causality, and compactness （finite duration）. We are able to determine rupture durations of four large earthquakes： the 2004 Sumatra-Andaman earthquake, the 2005 Nias event, the 2006 Java event, and the 2011 Tokuko earthquake. The rupture durations of the Sumatra-Andaman, Nias, and Tohuko events are found to be around 550, 1 i0, and 120 s respectively, consistent with previous studies. The rupture duration of the Java event is about 130 s, supporting that the Java event is a tsunami earthquake. The magnitudes of these earthquakes are found to depend on both the amplitude and the duration of the deconvolved waveforms, and can be approximated by integrating these waveforms.展开更多
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.
基金supported by Chinese Academy of Sciences (Grant No. KZCX2-YE-142)National Natural Science Foundation of China(Grant Nos. 40974034, 41174086, 41021003)Chinese Academy of Sciences (Grant No. KZCX2-YW-116)
文摘Earthquake magnitude and rupture duration are among the most important parameters characterizing an earthquake for the purpose of early tsunami warning. While they can be routinely determined from broadband P waveforms with iterative inver- sion procedures, the inversion procedures may fail when the rupture either lasts longer than the interval between P and later ar- rivals or requires too much time or human intervention. Little contaminated by later arrivals, high frequency P waves are useful for modeling earthquake source processes, though the envelope waveform is affected by strong scattering in lithosphere. With high frequency envelopes from aftershocks as Empirical Green＇s Function （EGF）, the coda effects can be removed and more accurate relative source time function （RSTF） of the main shock can be obtained. Assuming that RSTFs cannot be negative, we use the projected Landweber deconvolution method （PLD） to obtain high frequency RSTFs because PLD method has the ad- vantage of non-negativity, causality, and compactness （finite duration）. We are able to determine rupture durations of four large earthquakes： the 2004 Sumatra-Andaman earthquake, the 2005 Nias event, the 2006 Java event, and the 2011 Tokuko earthquake. The rupture durations of the Sumatra-Andaman, Nias, and Tohuko events are found to be around 550, 1 i0, and 120 s respectively, consistent with previous studies. The rupture duration of the Java event is about 130 s, supporting that the Java event is a tsunami earthquake. The magnitudes of these earthquakes are found to depend on both the amplitude and the duration of the deconvolved waveforms, and can be approximated by integrating these waveforms.
