Artificial Neural Networks for Prediction of Thermal Efficiency, Fuel Consumption and Exhaust Temperature in a CNG/Diesel Dual Fuel Engine
Publish place: 11th Iranian Student Conference on Electrical Engieering
Publish Year: 1387
نوع سند: مقاله کنفرانسی
زبان: English
View: 3,263
This Paper With 7 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
ISCEE11_158
تاریخ نمایه سازی: 15 اسفند 1386
Abstract:
During the last years a great deal of effort has been made for the reduction of pollutant emissions from direct injection diesel engines. Various solutions have been proposed, one of which is the use of gaseous fuels as a supplement for liquid diesel fuel. However, the combustion process in a dual fuel engine tends to display a complex combination of features of both compression and spark ignition engine operation. Therefore, the objective of this work is to investigate the ability of an artificial neural network model, using a back propagation learning algorithm, to predict specific fuel consumption, thermal efficiency and exhaust gas temperature of a dual fuel engine for various engine speeds and loads. The model predicted values are compared with corresponding experimental results. The comparison showed that the consistency between experimental and the network results are achieved by a mean absolute relative error less than 2%.
Keywords:
Neural networks , Dual Fuel Engine (DFE) , Specific fuel consumption , Thermal efficiency , Exhaust gas temperature
Authors
Mahdi Nejad
Amir Kabir University of Technology
Moallemi
Sahand University of Technology
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :