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Tytuł pozycji:

Fuzzy Logic-Based Novel Hybrid Fuel Framework for Modern Vehicles

Tytuł :
Fuzzy Logic-Based Novel Hybrid Fuel Framework for Modern Vehicles
Autorzy :
Muhammad Hamza Sarwar
Munam Ali Shah
Saif Ul Islam
Carsten Maple
Joel J. P. C. Rodrigues
Abdullah A. Alaulamie
Shafaq Mussadiq
Usman Tariq
Muhammad Nabeel Asghar
Pokaż więcej
Temat :
Fuzzy Logic
hybrid vehicle
electric vehicle
CO₂ emissions
fuel efficiency
Electrical engineering. Electronics. Nuclear engineering
TK1-9971
Źródło :
IEEE Access, Vol 8, Pp 160596-160606 (2020)
Wydawca :
IEEE, 2020.
Rok publikacji :
2020
Kolekcja :
LCC:Electrical engineering. Electronics. Nuclear engineering
Typ dokumentu :
article
Opis pliku :
electronic resource
Język :
English
ISSN :
2169-3536
Relacje :
https://ieeexplore.ieee.org/document/9143108/; https://doaj.org/toc/2169-3536
DOI :
10.1109/ACCESS.2020.3010067
Dostęp URL :
https://doaj.org/article/a5992bbe9da14615bbb7c9237ccb1d8c
Numer akcesji :
edsdoj.5992bbe9da14615bbb7c9237ccb1d8c
Czasopismo naukowe
The transport sector has proven to be the largest contributor to global CO2 emissions. To reduce CO2 emissions and improve mileage, the existing research has proposed different fuel models for vehicles such as Plug-in Hybrid Electric Vehicles (PHEVs), Electric Vehicles (EVs), solar and hydrogen Vehicles. However, these vehicles suffer from a range of issues and solutions are required to increase range, and improve charging. In this context, we propose A Novel Hybrid Fuel Framework for Modern Vehicles, to reduce CO2 emissions and increase vehicle mileage, by managing energy resources efficiently through the application of Fuzzy Logic. It considers three different energy sources i.e., gasoline, solar and electric power, to charge a vehicle, and suggest a modification in the architecture of EVs is made for the availability of all these energy resources. We use Visual Studio to implement fuzzy logic based algorithm designed to simulate the proposed system and added a small gasoline engine to the existing architecture of EVs to provide energy resources that overcome charging issues during long-range travel. We use the Statistical Package for Social Sciences (SPSS) tool to evaluate the performance of the proposed framework for CO2 emissions and fuel efficiency. The proposed framework achieves the best mileage of 57.6 Kilometers per liter (Km/l) with a 660 Cubic Centimeter (CC) gasoline engine which is 111.11% more efficient than existing frameworks. Moreover, CO2 emissions through our proposed framework are 41.52 Grams per Kilometer (G/Km) which are 53% lower than current frameworks. The proposed framework also improves the charging duration of batteries i.e., a 10 Kilowatt-Hour (KwH) battery can be charged in 1 hour and 15 minutes.

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