LAPSE:2018.0766
Published Article
LAPSE:2018.0766
A Fuzzy-Logic Power Management Strategy Based on Markov Random Prediction for Hybrid Energy Storage Systems
Yanzi Wang, Weida Wang, Yulong Zhao, Lei Yang, Wenjun Chen
October 23, 2018
Over the last few years; issues regarding the use of hybrid energy storage systems (HESSs) in hybrid electric vehicles have been highlighted by the industry and in academic fields. This paper proposes a fuzzy-logic power management strategy based on Markov random prediction for an active parallel battery-UC HESS. The proposed power management strategy; the inputs for which are the vehicle speed; the current electric power demand and the predicted electric power demand; is used to distribute the electrical power between the battery bank and the UC bank. In this way; the battery bank power is limited to a certain range; and the peak and average charge/discharge power of the battery bank and overall loss incurred by the whole HESS are also reduced. Simulations and scaled-down experimental platforms are constructed to verify the proposed power management strategy. The simulations and experimental results demonstrate the advantages; feasibility and effectiveness of the fuzzy-logic power management strategy based on Markov random prediction.
Keywords
battery, fuzzy logic, hybrid energy storage system (HESS), Markov random prediction, ultracapacitor (UC)
Suggested Citation
Wang Y, Wang W, Zhao Y, Yang L, Chen W. A Fuzzy-Logic Power Management Strategy Based on Markov Random Prediction for Hybrid Energy Storage Systems. (2018). LAPSE:2018.0766
Author Affiliations
Wang Y: National Key Laboratory of Vehicle Transmission, Beijing Institute of Technology, Beijing 100081, China
Wang W: National Key Laboratory of Vehicle Transmission, Beijing Institute of Technology, Beijing 100081, China
Zhao Y: National Key Laboratory of Vehicle Transmission, Beijing Institute of Technology, Beijing 100081, China
Yang L: Transmission System Section, Powertrain Department, Shanghai Automotive Industry Corporation Motor Commercial Vehicle Technical Center, Shanghai 200432, China
Chen W: The Forth Branch Company, Inner Mongolia First Machinery Group Co. Ltd., Baotou 014032, China
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Journal Name
Energies
Volume
9
Issue
1
Article Number
E25
Year
2016
Publication Date
2016-01-04
Published Version
ISSN
1996-1073
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PII: en9010025, Publication Type: Journal Article
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LAPSE:2018.0766
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doi:10.3390/en9010025
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Oct 23, 2018
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Oct 23, 2018
 
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Calvin Tsay
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