[1] PAHER Univ, Mech Engn Dept, Udaipur, Rajasthan, India
[2] Govt Engn Coll Dahod, Dahod, Gujarat, India
来源:
PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON FRONTIERS IN INTELLIGENT COMPUTING: THEORY AND APPLICATIONS, FICTA 2016, VOL 1
|
2017年
/
515卷
关键词:
Specific fuel consumption (SFC);
Compression ignition engine (CI);
Tyre pyrolysis oil (TPO);
Response surface methodology (RSM);
EMISSION CHARACTERISTICS;
PERFORMANCE;
OPTIMIZATION;
D O I:
10.1007/978-981-10-3153-3_2
中图分类号:
TP [自动化技术、计算机技术];
学科分类号:
0812 ;
摘要:
In this study, response surface methodology (RSM)-based prediction model was prepared for specific fuel consumption (SFC) as a response. A regression model was designed to predict SFC using RSM with central composite rotatable design (CCRD). In the development of regression models, injection timing, compression ratio, injection pressure, and engine load were considered as controlled variables. Injection pressure and compression ratio were observed as the most influencing variables for the SFC. The predicted SFC values and the succeeding verification experiments under the optimal conditions established the validity of the regression model.