一种新的锂离子电池多维容量估计与融合框架

Bo Jiang, Haifeng Dai, Wei Jiang, Fenglai Pei
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引用次数: 1

摘要

准确的容量估算在锂离子电池管理中起着至关重要的作用。本文提出了一种锂离子电池多维容量估计与融合的自适应框架,克服了传统估计方法不能有效利用更多有用信息的不足。首先,在充放电过程中,分别采用基于充电状态估计和基于增量容量分析估计两种估计方法获取电池容量。然后对不同估计的误差方差进行了分析和推导。提出了一种基于卡尔曼滤波的自适应融合方法,可以根据估计的误差方差自适应地结合两个估计。实验结果表明,该融合方法具有较好的估计精度和鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A novel framework of multi-dimension capacity estimation and fusion for lithium-ion battery
Accurate capacity estimation plays a vital role in lithium-ion battery management. In this paper, an adaptive framework of multi-dimension capacity estimation and fusion for lithium-ion battery is proposed, which can overcome the shortage that the conventional estimation cannot utilize more useful information effectively. Firstly, during the discharging and charging process, two estimation methods, including the state of charge based and incremental capacity analysis based estimation, are employed to acquire the battery capacity, respectively. Then, the error variance of different estimation is analyzed and deduced. An adaptive fusion method based on Kalman filter is proposed, which can combine the two estimates adaptably based on the error variance of estimation. The experimental results indicate the estimation of the proposed fusion method is relatively accurate and robust.
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