摘要
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．
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-fuel ratio of the lean burn engine is presented for the characteristics of the lean burn engine. With the engine control 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 burn 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 O. 2 AFR unit when the throttle body moves rapidly, completely better than the vehicle used electronic control unit （ECU）.
出处
《天津大学学报》
EI
CAS
CSCD
北大核心
2006年第B06期51-56,共6页
Journal of Tianjin University(Science and Technology)
基金
国家自然科学基金GM联合基金(50322261).
关键词
汽油机
稀薄燃烧
空燃比
发动机电子控制
神经网络
滑模变结构控制
gasoline engine
lean bum
air-fuel ratio
engine electronic control system
neural network
sliding mode variable structure control
