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. ZHANG Anan,XIE Linxing,YANG Wei.Research on Lithium Battery Life Prediction Model Based on CNN-GRU Combination Neural Network[J].Electrical Measurement & Instrumentation,2025,62(7):77-84.
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 Combination Neural Network
It is difficult to obtain direct performance parameters such as lithium battery capacity and internal resistance, 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 and gated recurrent unit is proposed . Firstly, four indirect health factors including constant current charging time interval, constant voltage charging time interval, discharge temperature peak time and cycle times are extracted from lithium battery charging and discharging experiments, and the Pearson and Spearman correlation coefficients are established. Secondly, build a lithium battery life prediction model based on CNN-GRU combined neural network. Finally, the rationality 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 to verify the superiority and effectiveness of the proposed model.
