摘要
天然气发动机本身具有低排放的特点,所以不需要由排放参数反馈修正发动机的空燃比,减少了控制的反馈系统。传统的混合器式天然气发动机无法高精度地控制发动机的空燃比,采用神经网络控制理论对天然气发动机的空燃比实施控制,使其空燃比始终保持在理论空燃比高精度的状态,提高了天然气发动机的性能。以175F天然气发动机为例,试验结果表明:采用神经网络控制的天然气发动机的性能高于混合器式天然气发动机。
CNG engine itself has low exhaust gas, therefore it doesnt need parameter of exhaust gas to feed back to modify air-fuel ratio, so the feedback system of controlling is reduced. Traditional CNG engine with a mixer does not control its air-fuel ratio accurately, so neural networks is adopted for controlling air-fuel ratio of CNG engine so that its air-fuel ratio is always kept at academic value, and the engine performance is increased. For an example, the experimental result of 175F engine is showed. The performance of CNG engines based on neural networks is higher than that of traditional CNG engines with mixer.
出处
《小型内燃机与摩托车》
CAS
北大核心
2007年第2期37-39,61,共4页
Small Internal Combustion Engine and Motorcycle
关键词
神经网络
发动机
天然气
性能
Neural network, Engine, CNG, Performance
