山东电力技术2026，Vol.53Issue(2)：98-109,12.DOI:10.20097/j.cnki.issn1007-9904.250471
基于部分满充放电数据的锂离子电池梯次利用SOH估计
SOH Estimation of Lithium-ion Batteries in Echelon Utilization Based on Partial Full Charge-discharge Data
摘要
Abstract
Accurate and efficient state of health(SOH)estimation of retired lithium-ion batteries in echelon utilization is crucial for maximizing their value throughout the entire lifecycle.Existing studies predominantly focus on improving estimation accuracy and reducing time and energy consumption,while overlooking equipment,experimental,and implementation costs,thus lacking engineering considerations.This research is conducted around feature selection,model development,and charging-discharging strategy optimization.Firstly,four effective peak-related health features are extracted from the incremental capacity curve during partial discharge after a full charge.Secondly,echelon utilization SOH estimation is achieved based on a deep feedforward neural network.The proposed method achieves root mean square error below 3.85%and mean absolute error below 3.65%in tests across multiple temperatures and battery types,with a maximum error of 2.85%for LiFePO4 batteries,demonstrating high accuracy,robustness,and adaptability.Furthermore,combining the proposed method,a SOH estimation charge-discharge scheme considering storage and reuse is developed.While ensuring estimation accuracy,it fully aligns with the practical application scenarios in echelon utilization,significantly reducing time,energy,equipment,experimental,and implementation expenses.The minimum energy consumption is approximately 40%of the total battery energy,providing novel insights and implementation pathways for SOH estimation in echelon utilization.关键词
锂离子电池/梯次利用/深度学习/健康状态Key words
lithium-ion batteries/echelon utilization/deep learning/state of health分类
信息技术与安全科学引用本文复制引用
魏峰,李中原,王新栋,董政..基于部分满充放电数据的锂离子电池梯次利用SOH估计[J].山东电力技术,2026,53(2):98-109,12.基金项目
国网山东省电力公司科技项目"新型电力系统微网应急供电保障技术研发与应用"(2024A-087). Science and Technology Project of State Grid Shandong Electric Power Company"Research and Application of Emergency Power Supply Guarantee Technology for Microgrids in New Power Systems"(2024A-087). （2024A-087）
