【摘要】 为了提高汽油机空燃比控制精度,满足动力性、经济性与排放性能要求,对汽油机加速瞬态工况油膜动态效应补偿技术进行研究。采用Elman神经网络对油膜参数进行辨识,通过仿真软件建立了汽油机油膜加速瞬态补偿器模型。基于mototron快速原型开发平台对设计的油膜补偿器模型进行策略移植、下载与标定,并通过离线仿真和试验进行验证。结果表明:Elman神经网络可以对汽油机油膜参数进行准确辨识,并且可以消除油膜动态效应对空燃比的影响,油膜补偿器能对汽油机加速瞬态工况下喷油进行有效补偿,更好的控制发动机加速瞬态过程中的空燃比。更多还原

【Abstract】 A method of oil film dynamic compensation technology for gasoline engine in the acceleration transient condition was studied in order to improve the Air-Fuel Ratio( AFR) control accuracy and meet the requirements of gasoline engine power,economy and emission properties. The parameters of oil film were identified by using the Elman neural networks; an oil film compensator model for gasoline engine in the acceleration transient condition was established by simulation software. Based on MotoTron rapid prototyping development platform,the oil film compensator model was transplanted,downloaded,calibrated,and verified by simulation and experiment. The results show that the Elman neural network can identify the parameters of oil film of gasoline engine,and can eliminate the oil film dynamic effect on the AFR; the oil film compensator can compensate effectively for injection of gasoline engine; and AFR can be controlled effectively in the acceleration transient conditions.更多还原