基于粒子群算法的锂电池多阶恒流充电方法  

Multi-order constant current charging method of lithium battery based on particle swarm optimization algorithm

作　　者：何佳琦 张春阳 周坤 HE Jiaqi;ZHANG Chunyang;ZHOU Kun(School of Information Engineering,Henan University of Science and Technology,Luoyang Henan 471023,China;Power Electronic Device and System Engineering Laboratory of Henan Province,Luoyang Henan 471023,China)

机构地区：[1]河南科技大学信息工程学院,河南洛阳471023 [2]电力电子装置与系统河南省工程实验室,河南洛阳471023

出　　处：《电源技术》2023年第10期1298-1302,共5页Chinese Journal of Power Sources

基　　金：国家自然科学基金项目(61971339);河南省自然科学基金项目(202300410148)。

摘　　要：为了解决恒流恒压充电速度慢,充电过程中锂电池温升大等问题,提出了一种将粒子群算法和多阶恒流充电模型相结合的方法来对锂电池充电技术进行优化,此方法不依赖于锂电池的机理模型,以充入电量、充电时间和充电能量效率为目标函数,找到最优电流组合,从而提高充电性能。实际工况下的实验结果表明,所采用的优化充电方法比传统的恒流恒压充电方法的充电时间缩短了415 s,充电能量效率提高了0.37%,最高温升降低了0.6℃,达到了提高锂电池充电性能的目的。In order to solve the problems of slow charging speed of constant current and constant voltage,and high temperature rise of lithium battery during charging,a method combining particle swarm optimization algorithm and multi-order constant current charging model was proposed to optimize the charging technology of lithium battery.This method does not depend on the mechanism model of lithium battery.The optimal current combination could be found under the constraints of the charging amount,charging time and charging energy efficiency,thus improving the charging performance.The experimental results under actual conditions show that the optimized charging method reduces the charging time by 415 s,increases the charging energy efficiency by 0.37%,and reduces the maximum temperature rise by 0.6℃compared with the traditional constant-current and constant-voltage charging method,thus optimizing the charging performance of lithium battery.

关 键 词：锂电池 多阶恒流充电模型 粒子群算法 最优电流组合 

分 类 号：TM912[电气工程—电力电子与电力传动]