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Research of Ant Colony Optimized Adaptive Control Strategy for Hybrid Electric Vehicle
Joint Authors
Baozhen, Yao
Li, Linhui
Huang, Haiyang
Chang, Jing
Zheng, Ning’an
Zhou, Yafu
Lian, Jing
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-08-28
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Energy management control strategy of hybrid electric vehicle has a great influence on the vehicle fuel consumption with electric motors adding to the traditional vehicle power system.
As vehicle real driving cycles seem to be uncertain, the dynamic driving cycles will have an impact on control strategy’s energy-saving effect.
In order to better adapt the dynamic driving cycles, control strategy should have the ability to recognize the real-time driving cycle and adaptively adjust to the corresponding off-line optimal control parameters.
In this paper, four types of representative driving cycles are constructed based on the actual vehicle operating data, and a fuzzy driving cycle recognition algorithm is proposed for online recognizing the type of actual driving cycle.
Then, based on the equivalent fuel consumption minimization strategy, an ant colony optimization algorithm is utilized to search the optimal control parameters “charge and discharge equivalent factors” for each type of representative driving cycle.
At last, the simulation experiments are conducted to verify the accuracy of the proposed fuzzy recognition algorithm and the validity of the designed control strategy optimization method.
American Psychological Association (APA)
Li, Linhui& Huang, Haiyang& Lian, Jing& Baozhen, Yao& Zhou, Yafu& Chang, Jing…[et al.]. 2014. Research of Ant Colony Optimized Adaptive Control Strategy for Hybrid Electric Vehicle. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1044103
Modern Language Association (MLA)
Li, Linhui…[et al.]. Research of Ant Colony Optimized Adaptive Control Strategy for Hybrid Electric Vehicle. Mathematical Problems in Engineering No. 2014 (2014), pp.1-10.
https://search.emarefa.net/detail/BIM-1044103
American Medical Association (AMA)
Li, Linhui& Huang, Haiyang& Lian, Jing& Baozhen, Yao& Zhou, Yafu& Chang, Jing…[et al.]. Research of Ant Colony Optimized Adaptive Control Strategy for Hybrid Electric Vehicle. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1044103
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1044103