A new control strategy for energy management in Plug-in Hybrid Electric Vehicles based on Fuzzy Cognitive Maps

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

ELIASI HOSSEIN; Ghoreyshi Mahnaz

Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: JOURNAL OF ENERGY MANAGEMENT Year:2019 | Volume:9 | Issue:3 Page(s): 14-25

Download Full-Text

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Verion

View:

585

Download:

Cites:

Information Journal Paper

Title

A new control strategy for energy management in Plug-in Hybrid Electric Vehicles based on Fuzzy Cognitive Maps

Author(s)

ELIASI HOSSEIN | Ghoreyshi Mahnaz | Issue Writer Certificate

Keywords

Plug-in Hybrid Electric VehiclesQ1

Fuzzy Cognitive MapsQ1

Supervisory ControlQ1

Energy ManagementQ1

State of ChargeQ1

Abstract

In this paper, a new control strategy for Energy Management in Plug-in Hybrid Electric Vehicles (PHEVs) using Fuzzy Cognitive Map (FCM) is presented. In this strategy, FCM is used as a Supervisory Control such that the State of Charge (SoC) of the battery is kept in the acceptable range and fuel consumption per kilometer is reduced, in addition to providing the request power. Since this method does not need to have an accurate model of the system, it has lower computational complexity in determining the control law and its implementation is easier than the classical methods. In this paper, the PHEV is series-parallel. For analysis the performance of the proposed control strategy, three actual and standard driving cycles and a typical urban driving cycle based on the actual traffic condition in Tehran city, have been used. Simulation results show the proposed control strategy provides the request power, reduceing the fuel consumption and keeps the SoC in high level, in comparison to conventional Fuzzy Controller.

Cites

No record.

References

No record.

Cite

APA: Copy

ELIASI, HOSSEIN, & Ghoreyshi, Mahnaz. (2019). A new control strategy for energy management in Plug-in Hybrid Electric Vehicles based on Fuzzy Cognitive Maps. JOURNAL OF ENERGY MANAGEMENT, 9(3 ), 14-25. SID. https://sid.ir/paper/223772/en

Vancouver: Copy

ELIASI HOSSEIN, Ghoreyshi Mahnaz. A new control strategy for energy management in Plug-in Hybrid Electric Vehicles based on Fuzzy Cognitive Maps. JOURNAL OF ENERGY MANAGEMENT[Internet]. 2019;9(3 ):14-25. Available from: https://sid.ir/paper/223772/en

IEEE: Copy

HOSSEIN ELIASI, and Mahnaz Ghoreyshi, “A new control strategy for energy management in Plug-in Hybrid Electric Vehicles based on Fuzzy Cognitive Maps,” JOURNAL OF ENERGY MANAGEMENT, vol. 9, no. 3 , pp. 14–25, 2019, [Online]. Available: https://sid.ir/paper/223772/en

Related Journal Papers