Design of Energy Management Strategy for Hybrid Electric Vehicles Based on Genetic Fuzzy Control

Fei Chen; Hehui Xie; Zhengjie Zhang; Yaoguang Cao; Yang Hua; Shichun Yang

doi:10.1109/CAC48633.2019.8997423

Design of Energy Management Strategy for Hybrid Electric Vehicles Based on Genetic Fuzzy Control

Fei Chen
, Hehui Xie
, Zhengjie Zhang
, Yaoguang Cao
, Yang Hua
, Shichun Yang

School of Transportation Science and Engineering

Beihang University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

A fuzzy control strategy which can realize the reasonable distribution of demand torque between engine and motor is designed for parallel hybrid electric vehicles. Subsequently, taking the comprehensive consideration of fuel economy and emission as multi-objective, the partition of the membership function of fuzzy controller is optimized by genetic algorithm. The results show that, due to the application of genetic algorithm to the fuzzy control strategy, the fuel consumption, HC emission, CO emission and NOx emission under the CYC-UDDS driving cycle can be decreased by 1.67%, 1.45%, 0.62% and 5.06%, respectively.

Original language	English
Title of host publication	Proceedings - 2019 Chinese Automation Congress, CAC 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	4980-4984
Number of pages	5
ISBN (Electronic)	9781728140940
DOIs	https://doi.org/10.1109/CAC48633.2019.8997423
State	Published - Nov 2019
Event	2019 Chinese Automation Congress, CAC 2019 - Hangzhou, China Duration: 22 Nov 2019 → 24 Nov 2019

Publication series

Name	Proceedings - 2019 Chinese Automation Congress, CAC 2019

Conference

Conference	2019 Chinese Automation Congress, CAC 2019
Country/Territory	China
City	Hangzhou
Period	22/11/19 → 24/11/19

Keywords

Fuzzy Control
Genetic algorithm
Hybrid electric vehicle
Multi-objective optimization

Access to Document

10.1109/CAC48633.2019.8997423

Cite this

Chen, F., Xie, H., Zhang, Z., Cao, Y., Hua, Y., & Yang, S. (2019). Design of Energy Management Strategy for Hybrid Electric Vehicles Based on Genetic Fuzzy Control. In Proceedings - 2019 Chinese Automation Congress, CAC 2019 (pp. 4980-4984). Article 8997423 (Proceedings - 2019 Chinese Automation Congress, CAC 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CAC48633.2019.8997423

@inproceedings{8863b5bb3e9a4a7aa192f93ec6e9cfbc,

title = "Design of Energy Management Strategy for Hybrid Electric Vehicles Based on Genetic Fuzzy Control",

abstract = "A fuzzy control strategy which can realize the reasonable distribution of demand torque between engine and motor is designed for parallel hybrid electric vehicles. Subsequently, taking the comprehensive consideration of fuel economy and emission as multi-objective, the partition of the membership function of fuzzy controller is optimized by genetic algorithm. The results show that, due to the application of genetic algorithm to the fuzzy control strategy, the fuel consumption, HC emission, CO emission and NOx emission under the CYC-UDDS driving cycle can be decreased by 1.67\%, 1.45\%, 0.62\% and 5.06\%, respectively.",

keywords = "Fuzzy Control, Genetic algorithm, Hybrid electric vehicle, Multi-objective optimization",

author = "Fei Chen and Hehui Xie and Zhengjie Zhang and Yaoguang Cao and Yang Hua and Shichun Yang",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 Chinese Automation Congress, CAC 2019 ; Conference date: 22-11-2019 Through 24-11-2019",

year = "2019",

month = nov,

doi = "10.1109/CAC48633.2019.8997423",

language = "英语",

series = "Proceedings - 2019 Chinese Automation Congress, CAC 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "4980--4984",

booktitle = "Proceedings - 2019 Chinese Automation Congress, CAC 2019",

address = "美国",

}

Chen, F, Xie, H, Zhang, Z, Cao, Y, Hua, Y & Yang, S 2019, Design of Energy Management Strategy for Hybrid Electric Vehicles Based on Genetic Fuzzy Control. in Proceedings - 2019 Chinese Automation Congress, CAC 2019., 8997423, Proceedings - 2019 Chinese Automation Congress, CAC 2019, Institute of Electrical and Electronics Engineers Inc., pp. 4980-4984, 2019 Chinese Automation Congress, CAC 2019, Hangzhou, China, 22/11/19. https://doi.org/10.1109/CAC48633.2019.8997423

Design of Energy Management Strategy for Hybrid Electric Vehicles Based on Genetic Fuzzy Control. / Chen, Fei; Xie, Hehui; Zhang, Zhengjie et al.
Proceedings - 2019 Chinese Automation Congress, CAC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 4980-4984 8997423 (Proceedings - 2019 Chinese Automation Congress, CAC 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Design of Energy Management Strategy for Hybrid Electric Vehicles Based on Genetic Fuzzy Control

AU - Chen, Fei

AU - Xie, Hehui

AU - Zhang, Zhengjie

AU - Cao, Yaoguang

AU - Hua, Yang

AU - Yang, Shichun

PY - 2019/11

Y1 - 2019/11

N2 - A fuzzy control strategy which can realize the reasonable distribution of demand torque between engine and motor is designed for parallel hybrid electric vehicles. Subsequently, taking the comprehensive consideration of fuel economy and emission as multi-objective, the partition of the membership function of fuzzy controller is optimized by genetic algorithm. The results show that, due to the application of genetic algorithm to the fuzzy control strategy, the fuel consumption, HC emission, CO emission and NOx emission under the CYC-UDDS driving cycle can be decreased by 1.67%, 1.45%, 0.62% and 5.06%, respectively.

AB - A fuzzy control strategy which can realize the reasonable distribution of demand torque between engine and motor is designed for parallel hybrid electric vehicles. Subsequently, taking the comprehensive consideration of fuel economy and emission as multi-objective, the partition of the membership function of fuzzy controller is optimized by genetic algorithm. The results show that, due to the application of genetic algorithm to the fuzzy control strategy, the fuel consumption, HC emission, CO emission and NOx emission under the CYC-UDDS driving cycle can be decreased by 1.67%, 1.45%, 0.62% and 5.06%, respectively.

KW - Fuzzy Control

KW - Genetic algorithm

KW - Hybrid electric vehicle

KW - Multi-objective optimization

UR - https://www.scopus.com/pages/publications/85080067612

U2 - 10.1109/CAC48633.2019.8997423

DO - 10.1109/CAC48633.2019.8997423

M3 - 会议稿件

AN - SCOPUS:85080067612

T3 - Proceedings - 2019 Chinese Automation Congress, CAC 2019

SP - 4980

EP - 4984

BT - Proceedings - 2019 Chinese Automation Congress, CAC 2019

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2019 Chinese Automation Congress, CAC 2019

Y2 - 22 November 2019 through 24 November 2019

ER -

Chen F, Xie H, Zhang Z, Cao Y, Hua Y, Yang S. Design of Energy Management Strategy for Hybrid Electric Vehicles Based on Genetic Fuzzy Control. In Proceedings - 2019 Chinese Automation Congress, CAC 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 4980-4984. 8997423. (Proceedings - 2019 Chinese Automation Congress, CAC 2019). doi: 10.1109/CAC48633.2019.8997423

Design of Energy Management Strategy for Hybrid Electric Vehicles Based on Genetic Fuzzy Control

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