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. |
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 |
DOI: |
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 |
基金项目:国家自然科学基金项目(51476112) |
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摘要:针对某款单缸大排量摩托车发动机,在Matlab/Simulink中建立带油膜补偿器的基于BP神经网络进气量预估模型,对上述组成的空燃比控制模型进行了仿真研究。结果表明,基于BP神经网络的进气量预估控制模型能将超调量控制在10%以内,并能够在1.4 s内将混合气恢复至当量比,避免了传统PID控制可能出现的震荡情况,表明基于进气预估的空燃比控制效果良好;加入油膜补偿后,其空燃比超调量不超过5%,能够在1.2 s内将混合气恢复至当量比,说明加入油膜补偿前馈控制能够有效降低燃油传输动态特性带来的影响,提高控制精度。 |
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. |
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