摘要
车用汽油机稳态工况下废气排放与汽油机转速、负荷、空燃比和点火正时等影响因素之间是非线性关系 ,通过对汽油机试验排放数据的学习 ,建立起描述车用汽油机废气 HC,CO,NOx 排放与上述因素之间关系的 BP神经网络模型 。
The static exhaust emission performance of automotive gasoline engines is influenced by a few factors such as engine's crankshaft rotate speed, load, air/fuel ration and spark timing, etc, the relationship between those factors and the engine exhaust emission performance is nonlinear. A BP neural network was developed to describe the relationships, and the neural network model was trained by engine test data. This model can be used for forecasting exhaust emission and controlling A/F, spark timing to decrease exhaust emission.
出处
《湖南大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2002年第1期67-73,共7页
Journal of Hunan University:Natural Sciences
基金
湖南省教育厅青年教师项目 (0 0 B0 11)
湖南省自然科学基金资助项目 (98JJY2 0 3 9)
