南京大学学报(自然科学版) ›› 2021, Vol. 57 ›› Issue (4): 660670.doi: 10.13232/j.cnki.jnju.2021.04.015
• • 上一篇
摘要:
容量和内阻是评估锂离子电池健康状态和预测其剩余寿命的重要指标,然而电池容量和内阻难以直接在线测量.通过分析锂离子电池充电过程中电流和电压的变化特征后提取出两种健康因子,并且证明所提因子与电池容量高度相关,进一步建立了用于锂电池容量估计的两因子线性回归模型.在此基础上,通过结合BP (back propagation)神经网络和粒子群优化思想设计锂离子电池健康状态估计算法.考虑到锂电池的健康状态和剩余使用寿命之间存在一定的映射关系,因此再利用所提取的健康因子和其健康状态估计结果设计了锂电池的剩余使用寿命预测算法.实验结果表明,所提取的健康因子能够准确地进行电池容量估计并应用于在线评估锂离子电池的健康状态和预测其剩余使用寿命.
中图分类号:
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[1] | 章福平1,Hasuck Kim2 , Byungwoo Park3. 掺杂稀土元素的锉离子电池正极材料 LiCo1 _y Rey O2电化学性能[J]. 南京大学学报(自然科学版), 2012, 48(3): 343-350. |
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