Charging optimization in lithium-ion batteries based on temperature rise and charge time

Caiping Zhang, Jiuchun Jiang, Yang Gao, Weige Zhang, Qiujiang Liu and Xiaosong Hu

Applied Energy, 2017, vol. 194, issue C, 569-577

Abstract: Lithium-ion battery fast charging issues have become a main bottleneck of large-scale deployment of electric vehicles. This paper develops a polarization based charging time and temperature rise optimization strategy for lithium-ion batteries. An enhanced thermal behavior model is introduced to improve the solution accuracy at high charging current, in which the relationship between polarization voltage and charge current is addressed. Genetic algorithm (GA) is employed to search for the optimal charging current trajectories. The effects of weighting coefficients of charging time and temperature rise on battery charging performance are discussed. The charging time of the optimized charging protocol is reduced by 50%, and the associated temperature rise is almost identical, compared to 1/3C constant current-constant voltage (CC-CV) charging. Aging experiments demonstrate that the proposed charging method has a similar capacity retention ratio to that of 0.5CC-CV charging after 700 cycles, thereby accomplishing a good balance between charging speed and lifetime.

Keywords: Polarization; Temperature rise; Charging optimization; Lithium-ion batteries; Electric vehicle (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (35)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:194:y:2017:i:c:p:569-577

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DOI: 10.1016/j.apenergy.2016.10.059

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