An Adaptive Charging Strategy of Lithium-ion Battery for Loss Reduction with Thermal Effect Consideration

Ding, Yujie, Wu, Haimeng, Gao, Zhiwei and Zhang, Hailong (2021) An Adaptive Charging Strategy of Lithium-ion Battery for Loss Reduction with Thermal Effect Consideration. In: 2021 IEEE 1st International Power Electronics and Application Symposium (PEAS). IEEE, Piscataway, US, p. 9628459. ISBN 9781665413619, 9781665413596, 9781665413602

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With the increasing deployment of the electric vehicles, the study of advanced battery charging strategy has become of great significance to improve charging performance with reduced loss. This paper presents an optimized adaptive charging strategy for EV battery packs based on a developed system loss model. An electrical model integrated with thermal properties for the lithium-ion battery with cooling as well as a full loss model for the power converter have been included in this complete model. To reduce the overall loss of the charging system, the influence of temperature and varying internal resistance at different state of charge (SOC) have been considered to obtain an objective function. Moreover, an enhanced particle swarm optimization (PSO) algorithm is proposed and applied to speed up convergence time as well as enhance the precision of the solution. The results show that this proposed strategy can reduce the total loss by 4.01 and a 7.48 decrease of the charging time compared with the classical approach without applying this optimization.

Item Type: Book Section
Additional Information: Funding information: The authors would like to thank Department of Mathematics, Physics and Electrical Engineering, Northumbria University, for the full support and research funding. 1st IEEE International Power Electronics and Application Symposium , IEEE PEAS'2021; Shanghai, China; 12-15 Nov 2021
Uncontrolled Keywords: lithium-ion battery, charging strategy, loss minimisation, particle swarm optimization
Subjects: H600 Electronic and Electrical Engineering
H800 Chemical, Process and Energy Engineering
Department: Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Depositing User: John Coen
Date Deposited: 17 Sep 2021 13:12
Last Modified: 09 Feb 2022 12:26

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