- Tytuł:
- Fuel saving index assessment on driving behavior control system of prototype model using neural network
- Autorzy:
-
Munahar, Suroto
Triwiyatno, Aris
Munadi, M.
Setiavan, Joga Dharma - Powiązania:
- https://bibliotekanauki.pl/articles/2173934.pdf
- Data publikacji:
- 2022
- Wydawca:
- Polska Akademia Nauk. Czytelnia Czasopism PAN
- Tematy:
-
Fuel Saving Index
FSI
fuel consumption
stoichiometry
driving behaviour
neural network
wskaźnik oszczędności paliwa
zużycie paliwa
stechiometria
zachowanie podczas jazdy
sieć neuronowa - Opis:
- Efficient fuel consumption in the world is essential in automotive technology development due to the increase in vehicle usage and the decrease in global oil production. Several studies have been conducted to increase fuel consumption savings, Fuel Cells (FCs), the application of alternative energy vehicles and the Engine Control Unit (ECU) system. FCs do not require oil energy to propel the vehicle, so this technology promises to reduce energy consumption and emissions. However, this research still leaves problems. FCs are susceptible to short circuit hazards, and ownership costs are very high. Alternative energy applications produce less power, less responsive acceleration, and insufficient energy sources to enter mass production. The ECU application still has an orientation toward achieving stoichiometry values, so the increase in fuel efficiency has the potential to be improved. Driving behavior is a variable that has a close relationship with fuel consumption efficiency. However, research on driving behavior is only studied for implementation in autonomous car-following technologies, safety systems, charging needs characteristic of electric vehicles, emission controls, and display images on invehicle information systems. Meanwhile, research on driving behavior as a control system to improve fuel efficiency has not been carried out. To that end, this study proposes the use of driving behavior for a newly designed control system to improve fuel efficiency. The control system in this research is a prototype model to be assessed using the Fuel Saving Index (FSI) analysis. An artificial neural network is used to help the recognition of driving behavior. The results showed that the newly designed control system was categorized on scale IV of FSI. On this scale, the power generated by the engine is quite optimal when it is in the eco-scheme driving behavior. The driving behavior control system can significantly improve the efficiency of fuel consumption. Air to Fuel Ratio (AFR) is achieved above the stoichiometric value.
- Źródło:
-
Archives of Transport; 2022, 63, 3; 123--141
0866-9546
2300-8830 - Pojawia się w:
- Archives of Transport
- Dostawca treści:
- Biblioteka Nauki
Artykuł