稀燃汽油机空燃比滑模-神经网络控制及实验

提高电控汽油机空燃比控制精度是改善发动机燃油经济性、动力性和降低尾气污染的关键环节．针对稀薄燃烧汽油机的工作原理,提出了一个稀燃汽油机空燃比滑模-神经网络控制方案,并对方案中的各环节进行了详细描述．采用自行开发的发动机电控系统,在一台稀燃发动机上进行了实验,并对实验结果进行了分析．实验结果表明,采用滑模-神经网络方案对稀薄燃烧发动机空燃比进行控制,不仅可以提高准稳态时发动机的空燃比控制精度．而且可以降低过渡过程的空燃比超调．节气门急速变化时的空燃比超调最大为1个空燃比单位,最小为0．2个空燃比单位,大大优于车用电控系统的控制结果．

Sliding Mode-Neural Network Control for Air-Fuel Ratio of Lean Burn Gasoline Engine and Experiment Research

To enhance the controlling accuracy of engine air-fuel ratio(AFR),improve the fuel economy and powering ability and reduce the pollution of tail gas,a sliding mode-neural network control scheme for the air-fu- el ratio of the lean burn engine is presented for the characteristics of the lean burn engine.With the engine con- trol system developed by ourselves,the lean burn engine air-fuel ratio control experiments are carried out on a lean burn gasoline engine.The results show that applying sliding mode-neural network scheme to controling the air-fuel ratio of the lean bum engine,both the steady-state and transient air-fuel ratio control accuracy can be enhanced.The maximal overshoot of air-fuel ratio is 1 AFR unit and the minimal overshoot reduces to 0.2 AFR unit when the throttle body moves rapidly,completely better than the vehicle used electronic control unit (ECU).