摘要
动力电池在老化过程中出现容量衰减、内阻增大和一致性下降等一系列特征变化,虽然这些特征变化给退役电池梯次利用安全性带来巨大挑战,但也成为电池状态评估和筛选的重要依据。首先,分析国内外政策法规在推动和规范梯次利用发展中的作用,并结合工程实例剖析安全隐患,提出特征指标提取与处理方法在效率和精度方面的要求。其次,围绕“模型-测试-算法”框架,创新性地将特征指标提取与处理分为“侧重于效率”和“侧重于精度”两大类方法,探讨在特征指标提取和处理过程中,测试手段和智能算法如何提高效率;介绍多维特征指标提取和分阶段的特征指标应用的过程中,模型与算法如何提高精度。最后,结合政策文献要求,对各类方法进行总结和对比,为迎接2030年即将来临的“退役电池浪潮”提供理论依据。
During the aging process of power batteries,characteristic changes such as capacity degradation,increased internal resistance,and decreased consistency occur.Although these changes present significant challenges to the safety of retired battery(RB)cascade utilization,they also form an important basis for battery state assessment and screening.This paper first analyzes the role of domestic and international policies and regulations in promoting and regulating the development of cascade utilization and examines safety hazards using engineering examples.The requirements for the extraction and processing methods of characteristic indicators(CI)in terms of efficiency and accuracy are proposed.Focusing on the"model-testing-algorithm"framework,the extraction and processing of CI are innovatively divided into two major categories:"emphasizing efficiency"and"emphasizing accuracy."The paper discusses how testing methods and intelligent algorithms can improve efficiency in CI extraction and processing,and it introduces how models and algorithms can enhance accuracy in multi-dimensional CI extraction and phased application.Finally,in combination with policy document requirements,various methods are summarized and compared to provide a theoretical basis for the forthcoming"retired battery wave"expected around 2030.
作者
谢红伟
时玮
陈诗荣
施洪生
李华伟
焦学文
XIE Hongwei;SHI Wei;CHEN Shirong;SHI Hongsheng;LI Huawei;JIAO Xuewen(School of Electrical Engineering,Beijing Jiaotong University,Beijing 100004,China)
出处
《储能科学与技术》
北大核心
2025年第9期3581-3595,共15页
Energy Storage Science and Technology
关键词
退役电池
状态评估
梯次利用
特征指标
电池筛选
retired batteries(RB)
state assessment
cascade utilization
characteristic indicators(CI)
battery screening
作者简介
第一作者:谢红伟(1999-),男,硕士研究生,研究方向为退役电池梯次利用筛分,Email:23126375@bjtu.edu.cn;通信作者:施洪生,副教授,从事新能源应用及精密测量技术研究,E-mail:hshshi@bjtu.edu.cn。
