基于健康因子的锂电池剩余寿命预测方法

Remaining Life Prediction Method of Lithium Battery Based on Health Factors

分析了锂电池的容量衰退趋势,从锂电池的充放电过程参数中提取与容量高度相关的健康因子,构建了基于BP(Back Propagation)神经网络的锂电池剩余寿命预测模型。分别采用健康因子拼接和其他特征拼接作为预测输入,对试验结果进行评估,指出所提取的健康因子结合BP神经网络模型预测速度快、精度高,具有较好的应用价值。

The capacity decline trend of lithium batteries is analyzed.Health factors highly correlated with capacity were extracted from the charging and discharging process parameters of lithium batteries,and a residual life prediction model for lithium batteries based on BP(Back Propagation)neural network was constructed.Health factor stitching and other feature stitching were used as prediction inputs,respectively.The experimental results were evaluated,and it was pointed out that the extracted health factors combined with BP neural network model had fast prediction speed and high accuracy,and had good application value.