考虑充电条件的部分间隔锂离子电池在线容量估算

Jian Wang, Lijun Zhu, Xiaoyu Liu, Yutao Wang, Lujun Wang
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摘要

增量容量分析 (ICA) 广泛应用于锂离子电池健康评估和容量估算,传统上需要在标准充放电条件下投入大量时间。然而,在实际使用中,锂离子电池很少经历完整的循环。本研究引入了电池不同部分区间内的老化温度循环,整合了局部 ICA 曲线、峰值范围分析和增量斜率(IS)作为辅助特征。提取的部分增量容量曲线可作为健康状态(SOH)估计的特征。所提出的基于温度速率的 SOH 估算方法依赖于机理函数,分析温度、不同部分间隔、老化速率和老化之间的关系。在 FCB21700 电池上进行的实验测试表明,仅使用部分充电曲线就能准确估算出 SOH,平均误差低于 2.82%。通过调节充电和放电范围,该方法大大延长了电池的使用寿命,具有广泛的应用前景。
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Online capacity estimation for lithium-ion batteries in partial intervals considering charging conditions
Employed extensively for lithium-ion battery health assessment and capacity estimation, Incremental Capacity Analysis (ICA) traditionally requires substantial time investment under standard charge and discharge conditions. However, in practical usage, Li-ion batteries rarely undergo full cycles. This study introduces aging temperature cycles within different partial intervals of the battery, integrating local ICA curves, peak range analysis, and Incremental Slope (IS) as an auxiliary feature. The extracted partial incremental capacity curves serve as features for State of Health (SOH) estimation. The proposed temperature-rate-based SOH estimation method relies on a mechanistic function, analyzing relationships between temperature, different partial intervals, aging rate, and aging. Experimental tests on FCB21700 batteries demonstrate accurate SOH estimation using only partial charge curves, with an average error below 2.82%. By manipulating charging and discharging ranges, the method significantly extends battery lifespan, offering promising widespread applications.
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