数字技术与应用Issue(10)：31-32,2.
人工神经网络在甲醇发动机中的应用研究
万瑞军 1盛光宗 2沈继忱2
作者信息
- 1. 东北电力大学化学工程学院 吉林吉林 132012
- 2. 东北电力大学自动化工程学院 吉林吉林 132012
- 折叠
摘要
Abstract
The nozzles are respectively instal ed on the inlet pipes of the four cylinders which are spraying methanol, in order to realizing combustion mode for methanol-diesel hybrid engine. Combustion mode for methanol-diesel hybrid is compared with combustion mode for diesel only in this lab.Then using Levenberg-Marquardt to predict BSFC (break specific fuel consumption), exhaust emissions that are CO (carbon monoxide) and HC (unburned hydrocarbon), and AFR (airefuel ratio) which operates with methanol-diesel blend fuel and diesel, and compared with actual measured data analysis. The test results show that the LM learning ability to BSFC, CO, HC and AFR prediction is quite effective, and compared with the pure diesel fuel, methanol to improve the emission characteristics.关键词
甲醇/柴油/LM发动机性能/废气排放Key words
methanol/diesel/LM Engine performance/Exhaust emissions分类
能源科技引用本文复制引用
万瑞军,盛光宗,沈继忱..人工神经网络在甲醇发动机中的应用研究[J].数字技术与应用,2013,(10):31-32,2.
