遗传算法优化理论在航空锂电池SOC测算中的应用  

Application of Genetic Algorithm Optimization Theory in SOC Measurementof Aviation Lithium Batteries

作　　者：陈晓辉 周骏[1] 蒋超[1] CHEN Xiaohui;ZHOU Jun;JIANG Chao(Air Force Logistics University,Xuzhou 221000,China)

机构地区：[1]空军勤务学院,江苏徐州221000

出　　处：《科技创新与生产力》2024年第5期116-120,共5页Sci-tech Innovation and Productivity

摘　　要：本研究基于遗传算法优化的控制理论,探讨了其在航空锂电池SOC测算中的应用。通过对锂离子电池充放电过程进行深入分析,结合遗传算法优化方法,提出了一种改进的SOC测算模型。该模型综合考虑了电池特性曲线、温度、电流等多种因素,提高了SOC测算的准确性和稳定性。本研究不仅在理论上对SOC测算进行了深入研究,还通过实验验证了所提方法的有效性,为锂离子电池的精准管理提供了重要支持。Based on the control theory optimized by genetic algorithm,this study discusses its application in the SOC measurement of aviation lithium batteries.Through the in-depth analysis of the charging and discharging process of lithium-ion batteries,combined with the genetic algorithm optimization method,an improved SOC calculation model is proposed.The model comprehensively considers various factors such as battery characteristic curve,temperature,and current,which improves the accuracy and stability of SOC measurement.This study not only conducts in-depth research on SOC measurement in theory,but also verifies the effectiveness of the proposed method through experiments,which provides important support for the accurate management of lithium-ion batteries.

关 键 词：锂离子电池 SOC测算 遗传算法 控制理论 

分 类 号：TM911[电气工程—电力电子与电力传动] TP301.6[自动化与计算机技术—计算机系统结构] TB114.2[自动化与计算机技术—计算机科学与技术] O231[理学—运筹学与控制论]