摘要
基于阿伦尼乌斯方程和神经网络算法,以温度为加速应力,开展了锂氟化碳电池(Li/CF_(x))加速贮存寿命模型的建立和研究。在基于阿伦尼乌斯方程的加速寿命模型中,模型计算值与实测数据结果准确率达到99%以上。在基于神经网络算法的模型中,少量的数据量训练即实现准确率达到85%,为锂原电池的寿命预测提供了有效指导。
Based on Arrhenius equation and neural network algorithm,the accelerated storage life model of lithium carbon fluoride battery(Li/CF_(x))was established and studied with temperature as the accelerated stress.In the accelerated life model based on Arrhenius equation,the accuracy of the calculated value of the model and the measured data was more than 99%.In the model based on neural network algorithm,a small amount of data training could achieve an accuracy of 85%,which provided effective guidance for the life prediction of lithium primary battery.
作者
郑海山
苏晓倩
谢欣
孟云
张洋
ZHENG Haishan;SU Xiaoqian;XIE Xin;MENG Yun;ZHANG Yang(Tianjin Institute of Power Sources,Tianjin 300384,China;The Third Military Representative Office of Kongzhuang Stationed in Tianjin,Tianjin 300000,China)
出处
《电源技术》
CAS
北大核心
2023年第3期308-311,共4页
Chinese Journal of Power Sources
关键词
锂氟化碳电池
贮存寿命模型
阿伦尼乌斯方程
神经网络算法
lithium carbon fluoride battery
storage life model
Arrhenius equation
neural network algorithm
