机械制造与自动化2026，Vol.55Issue(2)：101-107,7.DOI:10.19344/j.cnki.issn1671-5276.2026.02.020
基于SSA-SVR模型的锂离子电池剩余容量预测
Prediction of Remaining Capacity of Lithium-Ion Batteries Based on SSA-SVR Model
摘要
Abstract
This study predicts the remaining capacity of lithium-ion batteries by the SSA-SVR algorithm,and elabrates the basic principles of Support Vector Regression(SVR).Sparrow Search Algorithm(SSA)is utilized for global optimization of key parameters in S VR to enhance the precision of battery remaining life prediction.A SSA-SVR model is established,pre-testing is conducted using battery data from NASA PCoE demonstrate that SSA-SVR algorithm has better predictive accuracy and greater generalization capability.research center,and a comparison with standard SVR and genetic algorithm-based SVR prediction results is performed.关键词
锂离子电池/剩余容量/支持向量机/麻雀搜索算法Key words
lithium-ion battery/remaining capacity/support vector machine/sparrow search algorithm分类
信息技术与安全科学引用本文复制引用
宋健,李明林..基于SSA-SVR模型的锂离子电池剩余容量预测[J].机械制造与自动化,2026,55(2):101-107,7.基金项目
国家自然科学基金资助项目(11372074) （11372074）
