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Battery optimal charging strategy based on a coupled thermoelectric model
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Liu, Kailong, Li, Kang, Yang, Zhile, Zhang, Cheng and Deng, Jing (2016) Battery optimal charging strategy based on a coupled thermoelectric model. In: 2016 IEEE Congress on Evolutionary Computation (CEC), Vancouver, Canada, 24-29 Jul 2016. Published in: 2016 IEEE Congress on Evolutionary Computation (CEC) pp. 5084-5091. ISBN 9781509006236. doi:10.1109/CEC.2016.7748334
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Official URL: http://dx.doi.org/10.1109/CEC.2016.7748334
Abstract
Battery charging strategy is a key issue in battery management system to ensure good battery performance and safe operation during the charging process. In this paper, a novel battery optimal charging strategy is proposed by applying the TLBO algorithm to a LiFeP04 battery for an optimal charging based on a coupled thermoelectric model. A specific dual-objective function including battery charging time and temperature rise (both battery interior and surface) is formulated first. Then a battery optimal charging strategy is presented in detail by using the TLBO algorithm, aiming at finding a suitable constant-current-constant-voltage (CCCV) current profile to minimize the dual-objective function. Besides, the effects of different weights in dual-objective function on the optimal charging profile are analyzed. Simulation results demonstrate that the presented optimal charging strategy can provide effective and acceptable optimal charge current profile. The strategy can be also easily implemented to other battery types to effectively balance the battery charging time and battery temperature rise during charging process.
Item Type: | Conference Item (Paper) | ||||||
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Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering T Technology > TL Motor vehicles. Aeronautics. Astronautics |
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Divisions: | Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group) | ||||||
Library of Congress Subject Headings (LCSH): | Electric vehicles -- Batteries, Lithium ion batteries, Algorithms | ||||||
Journal or Publication Title: | 2016 IEEE Congress on Evolutionary Computation (CEC) | ||||||
Publisher: | IEEE | ||||||
ISBN: | 9781509006236 | ||||||
Book Title: | 2016 IEEE Congress on Evolutionary Computation (CEC) | ||||||
Official Date: | 21 November 2016 | ||||||
Dates: |
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Page Range: | pp. 5084-5091 | ||||||
DOI: | 10.1109/CEC.2016.7748334 | ||||||
Status: | Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||
Date of first compliant deposit: | 3 March 2017 | ||||||
Date of first compliant Open Access: | 3 March 2017 | ||||||
Funder: | Engineering and Physical Sciences Research Council (EPSRC), Guo jia zi ran ke xue ji jin wei yuan hui (China) [National Natural Science Foundation of China] (NSFC) | ||||||
Grant number: | EP/L00 1063/1 (EPSRC), 51361130153, 61533010 (NSFC) | ||||||
Conference Paper Type: | Paper | ||||||
Title of Event: | 2016 IEEE Congress on Evolutionary Computation (CEC) | ||||||
Type of Event: | Conference | ||||||
Location of Event: | Vancouver, Canada | ||||||
Date(s) of Event: | 24-29 Jul 2016 |
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