To ensure the control of the precision of air-fuel ratio(AFR)of port fuel injection(PFI)spark ignition(SI)engines,a chaos radial basis function(RBF)neural network is used to predict the air intake flow of the engine.T...To ensure the control of the precision of air-fuel ratio(AFR)of port fuel injection(PFI)spark ignition(SI)engines,a chaos radial basis function(RBF)neural network is used to predict the air intake flow of the engine.The data of air intake flow is proved to be multidimensionally nonlinear and chaotic.The RBF neural network is used to train the reconstructed phase space of the data.The chaos algorithm is employed to optimize the weights of output layer connection and the radial basis center of Gaussian function in hidden layer.The simulation results obtained from Matlab/Simulink illustrate that the model has higher accuracy compared to the conventional RBF model.The mean absolute error and the mean relative error of the chaos RBF model can reach 0.0017 and 0.48,respectively.展开更多
A one-dimensional pipe flow model of single-cylinder diesel engine is established to investigate the intake and exhaust flow characteristics of diesel engine in the condition of high power density(HPD).A space-lime co...A one-dimensional pipe flow model of single-cylinder diesel engine is established to investigate the intake and exhaust flow characteristics of diesel engine in the condition of high power density(HPD).A space-lime conservation element and solution element(CE/SE)method is used to derive the discrete equations of the partial differential equation for the intake and exhaust systems.The performance parameters of diesel engine with speed of 2100 r/min are simulated.The simulated results are in accordance with the experimental data.The effect of increased power density on charging coefficient is analyzed using a validated model.The results show that the charging coefficient is slowly improved with the increase in intake pressure,and is obviously reduced with the increase in engine speed.展开更多
基金Project(51176014)supported by the National Natural Science Foundation of ChinaProject(2016JJ2003)supported by Natural Scienceof Hunan Province,ChinaProject(KF1605)supported by Key Laboratory of Safety Design and Reliability Technology of Engineering Vehicle in Hunan Province,China。
文摘To ensure the control of the precision of air-fuel ratio(AFR)of port fuel injection(PFI)spark ignition(SI)engines,a chaos radial basis function(RBF)neural network is used to predict the air intake flow of the engine.The data of air intake flow is proved to be multidimensionally nonlinear and chaotic.The RBF neural network is used to train the reconstructed phase space of the data.The chaos algorithm is employed to optimize the weights of output layer connection and the radial basis center of Gaussian function in hidden layer.The simulation results obtained from Matlab/Simulink illustrate that the model has higher accuracy compared to the conventional RBF model.The mean absolute error and the mean relative error of the chaos RBF model can reach 0.0017 and 0.48,respectively.
文摘A one-dimensional pipe flow model of single-cylinder diesel engine is established to investigate the intake and exhaust flow characteristics of diesel engine in the condition of high power density(HPD).A space-lime conservation element and solution element(CE/SE)method is used to derive the discrete equations of the partial differential equation for the intake and exhaust systems.The performance parameters of diesel engine with speed of 2100 r/min are simulated.The simulated results are in accordance with the experimental data.The effect of increased power density on charging coefficient is analyzed using a validated model.The results show that the charging coefficient is slowly improved with the increase in intake pressure,and is obviously reduced with the increase in engine speed.
