M., Ghanbari and G., Najafi and B., Ghobadian and R., Mamat and M. M., Noor and A., Moosavian (2015) Adaptive Neuro-Fuzzy Inference System (Anfis) to Predict Ci Engine Parameters Fueled with Nano-Particles Additive to Diesel Fuel. In: IOP Conference Series: Materials Science and Engineering, 3rd International Conference of Mechanical Engineering Research (ICMER 2015) , 18-19 August 2015 , Kuantan, Pahang. pp. 1-8., 100 (012070). ISSN 1757-8981 (Print); 1757-899X (Online)
![[img]](http://umpir.ump.edu.my/style/images/fileicons/application_pdf.png) |
PDF
ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM (ANFIS) TO PREDICT CI ENGINE PARAMETERS FUELED WITH NANO-PARTICLES ADDITIVE TO DIESEL FUEL.pdf Restricted to Repository staff only Download (549kB) | Request a copy |
|
|
PDF
fkm-2015-najafi- Adaptive Neuro-Fuzzy Inference System.pdf Available under License Creative Commons Attribution. Download (1MB) | Preview |
Abstract
This paper studies the use of adaptive neuro-fuzzy inference system (ANFIS) to predict the performance parameters and exhaust emissions of a diesel engine operating on nanodiesel blended fuels. In order to predict the engine parameters, the whole experimental data were randomly divided into training and testing data. For ANFIS modelling, Gaussian curve membership function (gaussmf) and 200 training epochs (iteration) were found to be optimum choices for training process. The results demonstrate that ANFIS is capable of predicting the diesel engine performance and emissions. In the experimental step, Carbon nano tubes (CNT) (40, 80 and 120 ppm) and nano silver particles (40, 80 and 120 ppm) with nano-structure were prepared and added as additive to the diesel fuel. Six cylinders, four-stroke diesel engine was fuelled with these new blended fuels and operated at different engine speeds. Experimental test results indicated the fact that adding nano particles to diesel fuel, increased diesel engine power and torque output. For nano-diesel it was found that the brake specific fuel consumption (bsfc) was decreased compared to the net diesel fuel. The results proved that with increase of nano particles concentrations (from 40 ppm to 120 ppm) in diesel fuel, CO2 emission increased. CO emission in diesel fuel with nano-particles was lower significantly compared to pure diesel fuel. UHC emission with silver nano-diesel blended fuel decreased while with fuels that contains CNT nano particles increased. The trend of NOx emission was inverse compared to the UHC emission. With adding nano particles to the blended fuels, NOx increased compared to the net diesel fuel. The tests revealed that silver & CNT nano particles can be used as additive in diesel fuel to improve combustion of the fuel and reduce the exhaust emissions significantly.
| Item Type: | Conference or Workshop Item (Lecture) |
|---|---|
| Uncontrolled Keywords: | Adaptive Neuro-Fuzzy Inference System (ANFIS); Nanodiesel fuel; diesel engine; CNT and Ag nano particles; Performance and emission parameters. |
| Subjects: | T Technology > TJ Mechanical engineering and machinery |
| Faculty/Division: | Faculty of Mechanical Engineering |
| Depositing User: | Mrs. Neng Sury Sulaiman |
| Date Deposited: | 30 Sep 2015 03:27 |
| Last Modified: | 30 Jan 2018 03:00 |
| URI: | http://umpir.ump.edu.my/id/eprint/10532 |
| Download Statistic: | View Download Statistics |
Actions (login required)
 |
View Item |