电测与仪表2025，Vol.62Issue(7)：77-84,8.DOI:10.19753/j.issn1001-1390.2025.07.009
基于CNN-GRU组合神经网络的锂电池寿命预测模型研究
Research on Lithium battery life prediction model based on CNN-GRU combined neural network
摘要
Abstract
It is difficult to obtain direct performance parameters such as lithium battery capacity and internal resist-ance,which leads to the problem of low accuracy of lithium battery life prediction.A lithium battery life prediction model based on a combined neural network of convolutional neural network(CNN)and gated recurrent unit(GRU)is proposed.Four indirect health factors including constant current charging time interval,constant voltage charging time interval,discharging temperature peak time and cycle times are extracted from lithium battery char-ging and discharging experiments,and the Pearson and Spearman correlation coefficients are established.And then,a lithium battery life prediction model is built based on CNN-GRU combined neural network.Finally,the ra-tionality of extracting health factors is verified by actual data,and the prediction results are compared with SVR model,long short-term memory(LSTM)model,GRU model,and CNN-LSTM model to verify the superiority and effectiveness of the proposed model.关键词
锂电池/健康因子/相关系数/卷积神经网络/门控循环单元Key words
Lithium battery/health factor/correlation coefficient/convolutional neural network/gated recur-rent unit分类
信息技术与安全科学引用本文复制引用
张安安,谢琳惺,杨威..基于CNN-GRU组合神经网络的锂电池寿命预测模型研究[J].电测与仪表,2025,62(7):77-84,8.基金项目
国家自然科学基金重点项目(52034006) （52034006）
四川省科技计划项目(2020YFQ0038,2020YFSY0037) （2020YFQ0038,2020YFSY0037）
