基于SSA-VMD-GRU的锂电池剩余寿命预测方法研究Life prediction of lithium battery based on SSA-VMD-GRU
丁德邻,张营,左洪福
摘要(Abstract):
锂离子电池性能在衰退过程中呈现非平稳性和非线性,寿命预测往往被再生容量所干扰,衰退趋势难以捕捉,进而影响寿命预测。针对该问题,以容量为特征,构建一种基于麻雀搜索算法优化变分模态分解和门控循环单元的锂离子电池寿命预测方法。首先,利用麻雀搜索算法优化了变分模态分解的分解层数和惩罚因子,再通过优化了的变分模态分解算法将锂电池容量分解为若干分量,最后引入门控循环单元预测所分解的若干分量,将若干预测结果进行集成。通过NASA电池数据集对所提方法进行验证,并与两种模型相比较,结果表明,该方法相较于另两种方法预测精度平均提升了60%。
关键词(KeyWords): 锂电池;变分模态分解;麻雀搜索算法;门控循环单元;剩余寿命预测
基金项目(Foundation): 国家自然科学基金与民航联合基金重点项目(U1933202)
作者(Author): 丁德邻,张营,左洪福
DOI: 10.14106/j.cnki.1001-2028.2023.0224
参考文献(References):
- [1] 徐佳宁,倪裕隆,朱春波.基于改进支持向量回归的锂电池剩余寿命预测[J].电工技术学报,2021,36(17):3693-3704.
- [2] 汪翔,李小波,吴浩,等.基于非线性维纳过程的电解电容剩余寿命预测[J].电子元件与材料,2023,42(3):334-340.
- [3] 孙丙香,任鹏博,陈育哲,等.锂离子电池在不同区间下的衰退影响因素分析及任意区间的老化趋势预测[J].电工技术学报,2021,36(3):666-674.
- [4] 倪裕隆.基于SVR的锂离子电池剩余有效寿命预测方法[D].吉林:东北电力大学,2020.
- [5] 王海洋,宋万清.结合混沌的长相关锂电池寿命预测方法[J].传感器与微系统,2021,40(7):32-34.
- [6] Yu J B.State of health prediction of lithium-ion batteries:Multiscale logic regression and gaussian process regression ensemble[J].Reliability Engineering and System Safety,2018,174:82-95.
- [7] 姚芳,张楠,黄凯.锂离子电池状态估算与寿命预测综述[J].电源学报,2020,18(3):175-183.
- [8] Ali M U,Zafar A,Nengroo S H,et al.Online remaining useful life prediction for lithium-ion batteries using partial discharge data features[J].Energies,2019,12(22):4366.
- [9] Bai G X,Wang P F,Hu C.A self-cognizant dynamic system approach for prognostics and health management[J].Journal of Power Sources,2015,278:163-174.
- [10] 吴菲,郑秀娟.基于PF-GPR算法的锂离子电池剩余使用寿命预测[J].武汉科技大学学报,2022,45(3):189-196.
- [11] Tang X,Yao K,Zou C,et al.Predicting battery aging trajectory via a migrated aging model and bayesian monte carlo method[J].Energy Procedia,2019,158:2456-2461.
- [12] Wang F K,Huang C Y,Mamo T.Ensemble model based on stacked long short-term memory model for cycle life prediction of lithium-ion batteries[J].Applied Sciences,2020,10(10):3549.
- [13] Zhu M Y,Ouyang Q,Wang Y,et al.Remaining useful life prediction of lithium-ion batteries:A hybrid approach of grey-markov chain model and improved gaussian process[J].IEEE Journal of Emerging and Selected Topics in Power Electronics,2023,11(1):143-153.
- [14] 邢子轩,张凡,武明虎,等.基于WD-GRU的锂离子电池剩余寿命预测[J].电源技术,2022,46(8):867-871.
- [15] Liu K,Shang Y,Ouyang Q.A data-driven approach with uncertainty quantification for predicting future capacities and remaining useful life of lithium-ion battery[J].IEEE Transactions on Industrial Electronics,2021,68(4):3170-3180.
- [16] 刘家豪,张宏伟,袁永军.基于LSTM和EIS的锂电池健康状态估计[J].传感器与微系统,2021,40(12):59-61.
- [17] 杨彦茹,温杰,史元浩,等.基于CEEMDAN和SVR的锂离子电池剩余使用寿命预测[J].电子测量与仪器学报,2020,34(12):197-205.
- [18] Yang Z S,Wang Y H,Kong C Z.Remaining useful life prediction of lithium-ion batteries based on a mixture of ensemble empirical mode decomposition and GWO-SVR model[J].IEEE Transactions on Instrumentation and Measurement,2021,70:2517011.
- [19] 王冉,后麒麟,石如玉,等.基于变分模态分解与集成深度模型的锂电池剩余寿命预测方法[J].仪器仪表学报,2021,42(4):111-120.
- [20] 吕明珠,刘世勋,苏晓明,等.基于自适应变分模态分解和包络谐噪比的滚动轴承早期退化检测[J].振动与冲击,2021,40(13):271-280.
- [21] 杜晔,王子萌,黎妹红.基于优化核极限学习机的工控入侵检测方法[J].信息网络安全,2021,21(2):1-9.