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.
|Number of pages||7|
|Publication status||Accepted/In press - 21 Aug 2021|
|Event||1st IEEE International Power Electronics and Application Symposium - Shanghai, China|
Duration: 12 Nov 2021 → 15 Nov 2021
|Conference||1st IEEE International Power Electronics and Application Symposium|
|Abbreviated title||IEEE PEAS'2021|
|Period||12/11/21 → 15/11/21|