Energy Management of Dual-Source Propelled Electric Vehicle using Fuzzy Controller Optimized via Genetic Algorithm

Saeed Khoobi; Abolfazl Halvaei; Amin Hajizadeh

doi:10.1109/PEDSTC.2016.7556884

Energy Management of Dual-Source Propelled Electric Vehicle using Fuzzy Controller Optimized via Genetic Algorithm

Saeed Khoobi, Abolfazl Halvaei, Amin Hajizadeh

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Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

7 Citationer (Scopus)

Abstract

Energy and power distribution between multiple energy sources of electric vehicles (EVs) is the main challenge to achieve optimum performance from EV. Fuzzy inference systems are powerful tools due to nonlinearity and uncertainties of EV system. Design of fuzzy controllers for energy management of EV relies too much on the expert experience and it may lead to sub-optimal performance. This paper develops an optimized fuzzy controller using genetic algorithm (GA) for an electric vehicle equipped with two power bank including battery and super-capacitor. The model of EV and optimized fuzzy controller are simulated in ADVISOR software. Developed method has been implemented on standard driving cycles and simulation results show the decrease on consumed power by developed controller compared with standard fuzzy controller.

Originalsprog	Engelsk
Titel	Proceedings of the 7th Power Electronics and Drive Systems Technologies Conference (PEDSTC), 2016
Antal sider	6
Forlag	IEEE Press
Publikationsdato	feb. 2016
Sider	338-343
ISBN (Elektronisk)	978-1-5090-0375-4
DOI	https://doi.org/10.1109/PEDSTC.2016.7556884
Status	Udgivet - feb. 2016
Begivenhed	Power Electronics, Drive Systems & Technologies Conference - , Iran Varighed: 16 feb. 2016 → 18 feb. 2016

Konference

Konference	Power Electronics, Drive Systems & Technologies Conference
Land/Område	Iran
Periode	16/02/2016 → 18/02/2016

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10.1109/PEDSTC.2016.7556884

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Citationsformater

@inproceedings{3a11024d698f41238af4e325f78ab6f5,

title = "Energy Management of Dual-Source Propelled Electric Vehicle using Fuzzy Controller Optimized via Genetic Algorithm",

abstract = "Energy and power distribution between multiple energy sources of electric vehicles (EVs) is the main challenge to achieve optimum performance from EV. Fuzzy inference systems are powerful tools due to nonlinearity and uncertainties of EV system. Design of fuzzy controllers for energy management of EV relies too much on the expert experience and it may lead to sub-optimal performance. This paper develops an optimized fuzzy controller using genetic algorithm (GA) for an electric vehicle equipped with two power bank including battery and super-capacitor. The model of EV and optimized fuzzy controller are simulated in ADVISOR software. Developed method has been implemented on standard driving cycles and simulation results show the decrease on consumed power by developed controller compared with standard fuzzy controller. ",

keywords = "Electric Vehicle (EV), Energy Management, Fuzzy Controller, Genetic Algorithm (GA), ADVISOR",

author = "Saeed Khoobi and Abolfazl Halvaei and Amin Hajizadeh",

year = "2016",

month = feb,

doi = "10.1109/PEDSTC.2016.7556884",

language = "English",

pages = "338--343",

booktitle = "Proceedings of the 7th Power Electronics and Drive Systems Technologies Conference (PEDSTC), 2016",

publisher = "IEEE Press",

note = "Power Electronics, Drive Systems & Technologies Conference, PEDSTC 2016 ; Conference date: 16-02-2016 Through 18-02-2016",

}

Khoobi, S, Halvaei, A & Hajizadeh, A 2016, Energy Management of Dual-Source Propelled Electric Vehicle using Fuzzy Controller Optimized via Genetic Algorithm. i Proceedings of the 7th Power Electronics and Drive Systems Technologies Conference (PEDSTC), 2016. IEEE Press, s. 338-343, Power Electronics, Drive Systems & Technologies Conference, Iran, 16/02/2016. https://doi.org/10.1109/PEDSTC.2016.7556884

Energy Management of Dual-Source Propelled Electric Vehicle using Fuzzy Controller Optimized via Genetic Algorithm. / Khoobi, Saeed; Halvaei, Abolfazl; Hajizadeh, Amin.
Proceedings of the 7th Power Electronics and Drive Systems Technologies Conference (PEDSTC), 2016. IEEE Press, 2016. s. 338-343.

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

TY - GEN

T1 - Energy Management of Dual-Source Propelled Electric Vehicle using Fuzzy Controller Optimized via Genetic Algorithm

AU - Khoobi, Saeed

AU - Halvaei, Abolfazl

AU - Hajizadeh, Amin

PY - 2016/2

Y1 - 2016/2

N2 - Energy and power distribution between multiple energy sources of electric vehicles (EVs) is the main challenge to achieve optimum performance from EV. Fuzzy inference systems are powerful tools due to nonlinearity and uncertainties of EV system. Design of fuzzy controllers for energy management of EV relies too much on the expert experience and it may lead to sub-optimal performance. This paper develops an optimized fuzzy controller using genetic algorithm (GA) for an electric vehicle equipped with two power bank including battery and super-capacitor. The model of EV and optimized fuzzy controller are simulated in ADVISOR software. Developed method has been implemented on standard driving cycles and simulation results show the decrease on consumed power by developed controller compared with standard fuzzy controller.

AB - Energy and power distribution between multiple energy sources of electric vehicles (EVs) is the main challenge to achieve optimum performance from EV. Fuzzy inference systems are powerful tools due to nonlinearity and uncertainties of EV system. Design of fuzzy controllers for energy management of EV relies too much on the expert experience and it may lead to sub-optimal performance. This paper develops an optimized fuzzy controller using genetic algorithm (GA) for an electric vehicle equipped with two power bank including battery and super-capacitor. The model of EV and optimized fuzzy controller are simulated in ADVISOR software. Developed method has been implemented on standard driving cycles and simulation results show the decrease on consumed power by developed controller compared with standard fuzzy controller.

KW - Electric Vehicle (EV)

KW - Energy Management

KW - Fuzzy Controller

KW - Genetic Algorithm (GA)

KW - ADVISOR

U2 - 10.1109/PEDSTC.2016.7556884

DO - 10.1109/PEDSTC.2016.7556884

M3 - Article in proceeding

SP - 338

EP - 343

BT - Proceedings of the 7th Power Electronics and Drive Systems Technologies Conference (PEDSTC), 2016

PB - IEEE Press

T2 - Power Electronics, Drive Systems & Technologies Conference

Y2 - 16 February 2016 through 18 February 2016

ER -

Energy Management of Dual-Source Propelled Electric Vehicle using Fuzzy Controller Optimized via Genetic Algorithm

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