[1]张 宇,徐 思. 基于改进布谷鸟算法的快速充电方法[J].湖北工业大学学报,2023,(1):33-37+42.
　ZHANG Yu,XU Si. Fast Charging Method based on Improved Cuckoo Algorithm[J].,2023,(1):33-37+42.
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 基于改进布谷鸟算法的快速充电方法()
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《湖北工业大学学报》[ISSN:1003-4684/CN:42-1752/Z]

卷:
期数:
2023年第1期
页码:
33-37+42
栏目:
出版日期:
2023-03-13

文章信息/Info

Title:
 Fast Charging Method based on Improved Cuckoo Algorithm
文章编号:
1003-4684(2023)01-0033-05
作者:
 张 宇;  徐 思
 湖北工业大学太阳能高效利用及储能运行控制湖北省重点实验室，湖北 武汉 430068
Author(s):
 ZHANG Yu; XU Si
 Hubei Key Laboratory of Solar Energy Efficient Utilization and Energy Storage Operation Control, Hubei Univ. of Tech., Wuhan 430068,China
关键词:
 ; 锂离子电池;  改进布谷鸟算法;  充电时间;  温升
Keywords:
 ; Lithium-ion battery;  improve the cuckoo algorithm;  charging time;  temperature rise
分类号:
TM912.9
文献标志码:
A
摘要:
 针对锂离子电池快速充电问题，提出了一种基于改进布谷鸟算法的快速充电方法。首先建立锂离子电池等效电路模型和热模型，然后以充电时间和温升为优化目标，采用多阶充电的方法，最后用改进布谷鸟算法搜索每个阶段的充电电流。讨论了充电时间和温升的权重系数对电池充电性能的影响，与传统布谷鸟算法相比，优化布谷鸟算法充电方法能够在温度升高几乎相同的情况下，充电时间减少约5%左右，平衡了充电速度和温升，延长了锂离子电池的使用寿命。
Abstract:
 In spite of the current rapid development of electric vehicles, the problem of rapid charging of lithium-ion batteries has become a bottleneck in the application. This paper presents a fast charging method based on an improved cuckoo algorithm. Firstly, the equivalent circuit model and thermal model of lithium-ion battery are established. Then a multi-step charging method is used with charging time and temperature rise as the optimization objectives. Finally, the improved cuckoo algorithm is used to search for the charging current at each stage. The influence of the weighting factors of charging time and temperature rise on the battery charging performance is discussed. Compared to the conventional cuckoo algorithm, the optimised cuckoo algorithm charging method is able to reduce the charging time by around 5% with almost the same temperature rise, balancing the charging speed and temperature rise and extending the life of the Li-ion battery.

参考文献/References:

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备注/Memo

备注/Memo:
［收稿日期］ 2021-12-18
［第一作者］ 张 宇（1972-），女，湖北松滋人，湖北工业大学教授，研究方向为光伏发电系统应用
［通信作者］ 徐 思（1994-），女，湖北武汉人，湖北工业大学硕士研究生，研究方向为储能
更新日期/Last Update: 2023-03-14