内燃机工程2018，Vol.39Issue(2)：1-8,8.DOI:10.13949/j.cnki.nrjgc.2018.02.001
基于BP神经网络进气预估的汽油机瞬态空燃比控制研究
Research on Gasoline Engine Transient Air-Fuel Ratio Control Based on Back Propagation Neural Network for Intake Estimation
摘要
Abstract
To develop the control of the transient air-fuel ratio of a single-cylinder motorcycle engine of large displacement,an intake quantity estimating model based on back propagation (BP)neural network and a fuel film compensation model were built with the Matlab/Simulink,and the simulation of air-fuel ratio control was conducted with the two models.The results indicate that the intake quantity estimating model can limit the overshoot of air-fuel ratio to less than 10%,and resume the mixture to homogeneous equivalence ratio in 1.4 s,avoiding the concussion that generally takes place in conventional proportion integration differentiation control.This illustrates that the air-fuel ratio control based on transient air flow prediction works well.Its combination with the fuel film compensation can make the air-fuel ratio overshoot decline to less than 5 % and the mixture resume to homogeneous equivalence ratio in 1.2 s.This shows that the introduction of fuel film compensation algorithm can significantly decrease the impact of dynamic fuel-transmission characteristic,improving the precision of air-fuel ratio control.关键词
内燃机/瞬态工况/空燃比控制/BP神经网络/进气量预估/油膜补偿Key words
IC engine/transient condition/air-fuel ratio control/BP neural network/air intake estimation/fuel film compensation分类
能源科技引用本文复制引用
胡春明,王旸,王齐英,刘娜,魏石峰..基于BP神经网络进气预估的汽油机瞬态空燃比控制研究[J].内燃机工程,2018,39(2):1-8,8.基金项目
国家自然科学基金项目(51476112)National Natural Science Foundation of China (51476112) （51476112）
