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基于局部充电曲线重构的锂离子电池健康状态估计

State of Health Estimation for Lithium-Ion Batteries Based on Partial Charging Curve Reconstruction

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中文摘要

为保障锂离子电池安全高效运行,精确估计健康状态(SOH)至关重要。针对现有研究多依赖完整或大范围充电曲线、在实际应用中难以获取的问题,本文提出了一种基于局部充电曲线重构的SOH估计新方法,有效提升了电池状态评估的实用性与准确性。

English Abstract

To guarantee the safe and efficient operation of lithium-ion batteries, it is crucial to precisely estimate the state of health (SOH) of batteries. However, most of the existing studies have primarily focused on complete or large-range charging curves, which are highly challenging to acquire in practical applications. To this end, a novel SOH estimation method based on partial charging curve recon...
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SunView 深度解读

该技术对阳光电源的PowerTitan和PowerStack等储能系统具有极高的应用价值。在实际电站运维中,电池往往难以充满,基于局部曲线的SOH估计能显著提升iSolarCloud平台对电池衰减的监测精度,无需等待电池完全充电即可完成评估。建议将该算法集成至BMS核心算法库中,以优化储能电站的寿命管理,提升系统全生命周期收益,并为电网侧及工商业储能项目的精细化运维提供技术支撑。