船电技术2026，Vol.46Issue(1)：8-13,18,7.
基于改进鹭鹰优化算法的锂电池RUL预测研究
Research on lithium battery Remaining Useful Life prediction based on an improved secretary bird optimization algorithm
摘要
Abstract
Aiming at the inherent nonlinearity and instability of lithium battery capacity degradation,which leads to the problem of difficult to improve the prediction accuracy of lithium battery RUL(Remaining Useful Life,RUL).In this paper,a lithium battery RUL prediction model based on ISBOA-LSTM is proposed.First,the outliers in the data are adjusted by the method of mean interpolation.Then,the Fuch mapping and Cauchy mutation strategies are invoked to optimize the Secretary Bird Optimization Algorithm(SBOA),and the improved Secretary Bird Optimization Algorithm(ISBOA)is utilized to optimize the parameter configuration of the LSTM network.Finally,the ISBOA-LSTM model is validated based on the NASA public dataset,and the results show that the proposed model exhibits higher prediction accuracy in lithium battery RUL prediction,and the root-mean-square error as well as the mean absolute error of the model can be as low as 0.0085 and 0.0064.关键词
鹭鹰优化算法/剩余使用寿命/锂电池Key words
Secretary bird optimization algorithm/remaining useful life/lithium-ion battery分类
信息技术与安全科学引用本文复制引用
宁佳伟,曾进辉,曾冠林,黄梓涵..基于改进鹭鹰优化算法的锂电池RUL预测研究[J].船电技术,2026,46(1):8-13,18,7.基金项目
国家自然科学基金项目,"多微电网互联电能变换器及其控制方法研究(52377185)". （52377185）
