Adaptive Optimal Charge Strategy for Lithium-ion Power Battery Based on Multi-Objective Algorithm

被引：1
|
作者：
Wang, Qiuting [1 ]
Wo, Qizhong [2 ]
Qi, Wei [1 ]
机构：
[1] Zhejiang Univ City Coll, Sch Informat & Elect Engn, Hangzhou, Peoples R China
[2] Inst Measurement Qual & Tech Supervis, Hangzhou, Peoples R China
来源：
JOURNAL OF CONTROL AUTOMATION AND ELECTRICAL SYSTEMS | 2021年 / 32卷 / 05期
关键词：
Lithium-ion power battery; Charge strategy; Multi-objective algorithm; Particle swarm optimization; Cutoff voltage; Inertia weight; PATTERN; SEARCH; ENERGY;
D O I：
10.1007/s40313-021-00759-0
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The lithium-ion power battery is widely used in energy management system of electric vehicles. Our study proposed an adaptive optimal charge strategy based on multi-objective particle swarm optimization algorithm. The basic principles of multi-objective algorithm are introduced and the physical performance of lithium-ion battery based on different charge mode is discussed. In our research, the internal charge resistance and charge capacity value are analyzed under different charge current. The simulation model of our new method is established and the parameters are calculated. The experiments are operated to verify the influence of the charge stage number, cutoff voltage and inertia weights. The results indicate that our new charge strategy can be applied to the field of grid energy storage and expand the application scope of lithium-ion power battery.
引用
收藏
页码：1408 / 1416
页数：9
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