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

Yujie Ding, Haimeng Wu, Zhiwei Gao, Hailong Zhang

Research output: Contribution to conferencePaperpeer-review

Abstract

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.
Original languageEnglish
Number of pages7
Publication statusAccepted/In press - 21 Aug 2021
Event1st IEEE International Power Electronics and Application Symposium - Shanghai, China
Duration: 12 Nov 202115 Nov 2021

Conference

Conference1st IEEE International Power Electronics and Application Symposium
Abbreviated titleIEEE PEAS'2021
CountryChina
CityShanghai
Period12/11/2115/11/21

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