Neural Network Control Method for Automotive Engine Air-fuel Ratio Based on Torque Demand and Generalized Prediction of Intake Volume
The combustion characteristics and temperature values were analyzed to control the air fuel ratio of auto-motive engines.However,the delay effect of the internal fuel injection process was ignored,resulting in a significant de-viation between the control results and the ideal value of the air fuel ratio.Therefore,a neural network control method for automotive engine air-fuel ratio based on torque demand and generalized prediction of intake volume is proposed.Based on torque demand analysis of automobile power coefficient,a generalized prediction of engine intake during fuel injection is made,and the fuel injection delay is compensated according to the predicted value.The air fuel ratio control law is opti-mized to achieve the control process.The experimental results show that the control results obtained after the application of the method in this article are very close to the ideal 14.7 air-fuel ratio,and the control effect is relatively high-quality,meeting the actual requirements of combustion quality for automotive engines.
Automotive engineEngine air-fuel ratioTorque demandGeneralized prediction of intake vol-umeNeural networksAir fuel ratio control
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