信息与控制2024，Vol.53Issue(1)：120-128,9.DOI:10.13976/j.cnki.xk.2023.2378
基于混合网络的锂离子电池健康状态与剩余使用寿命联合估计方法
Joint Estimation Method of State of Health and Remaining Useful Life for Lithium-ion Batteries Based on Hybrid Networks
摘要
Abstract
To efficiently and accurately predict the state of health(SOH)and remaining useful life(RUL)of lithium-ion batteries,we propose a hybrid network-based joint estimation method of lithium-ion batteries SOH and RUL.First,we develop a framework for the indirect health factor(HF)extraction of lithium batteries and form a convolutional neural network(CNN)-recurrent gated unit(GRU)battery SOH estimation model using a CNN and GRU with HF as the input and capacity as the output.Second,we build a CNN-GRU battery RUL prediction model using the SOH estimation results and the true SOH values to predict the RUL.Experimental results show that the maximum root mean square error of SOH estimation is 2.31％,and the RUL prediction error is 5.29％.Therefore,the method can comprehensively assess the SOH and RUL of lithium batteries.关键词
锂离子电池/健康状态/剩余使用寿命/混合网络Key words
lithium-ion battery/state of health/remaining useful life/hybrid network分类
动力与电气工程引用本文复制引用
朱振宇,高德欣..基于混合网络的锂离子电池健康状态与剩余使用寿命联合估计方法[J].信息与控制,2024,53(1):120-128,9.基金项目
山东省重点研发计划(2019GGX101012) （2019GGX101012）
山东省自然科学基金项目(ZR2022ME194) （ZR2022ME194）
