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当前位置：电气工程与自动化 > 2025年 4卷 (7)期

Open Access Article

Journal of Electrical Engineering and Automation. 2025; 4: (7) ; 68-73 ; DOI: 10.12208/j.jeea.20250237.

A review of health state assessment for retired power batteries in the context of cascade utilization
梯次利用背景下退役动力电池健康状态评估综述

作者： 陈梦婷 *

南京邮电大学物联网学院江苏南京

*通讯作者：陈梦婷,单位：南京邮电大学物联网学院江苏南京；

国家自然科学基金青年基金项目（项目编号：62503242）

发布时间: 2025-12-07 总浏览量: 76

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摘要

随着新能源汽车产业的快速发展，全球正迎来首轮动力电池退役潮。梯次利用作为实现退役电池价值最大化、缓解环境与资源压力的关键路径，其核心挑战在于如何保障电池在二次利用过程中的安全性与可靠性。本文系统综述了梯次利用背景下退役动力电池健康状态评估的研究现状，重点围绕三个核心层面展开：1. 剖析了电化学模型与等效电路模型等老化特征建模方法的优势与局限性，指出其在应对梯次电池高度异构性和复杂非线性老化时的不足；2. 探讨了模型参数辨识的技术路径，分析了实验驱动、数据驱动及智能算法在应对梯次电池参数高维、动态变化等挑战中的进展与瓶颈；3. 评述了基于直接测试、模型驱动及数据驱动的健康状态评估方法，并强调了新兴的物理信息神经网络等在融合物理机理与数据智能方面的潜力。最后，本文总结了该领域在多尺度耦合机理建模不足、参数动态辨识局限、健康评估方法可解释性差等方面面临的挑战，为未来研究方向提供了展望。

关键词： 梯次利用；退役动力电池；健康状态评估；电池建模

Abstract

With the rapid development of the new energy vehicle industry, the world is witnessing the first wave of power battery retirements. Battery cascade utilization, as a key pathway to maximizing the residual value of retired batteries and alleviating environmental and resource pressures, faces a core challenge—ensuring safety and reliability during secondary use. This paper provides a systematic review of research on health state assessment of retired power batteries in the context of cascade utilization, focusing on three key aspects. 1. It analyzes the advantages and limitations of aging feature modeling methods such as electrochemical models and equivalent circuit models, highlighting their inadequacy in addressing the high heterogeneity and nonlinear degradation of cascaded batteries. 2. It explores parameter identification approaches, summarizing the progress and bottlenecks of experimental-driven, data-driven, and intelligence-driven methods in handling high-dimensional and dynamically varying parameters. 3. It reviews health assessment methods based on direct testing, model-driven, and data-driven frameworks, emphasizing the potential of emerging physics-informed neural networks for integrating physical mechanisms with data intelligence. Finally, this paper summarizes the challenges in multi-scale mechanism modeling, dynamic parameter identification, and interpretability of health assessment methods, and provides insights into future research directions.

Key words： Cascade utilization; Retired power battery; Health state assessment; Battery modeling

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引用本文

陈梦婷, 梯次利用背景下退役动力电池健康状态评估综述[J]. 电气工程与自动化, 2025; 4: (7) : 68-73.

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