基于OCV滞后效应的扩展卡尔曼滤波LiFePO4/C电池荷电状态估计

Jonghoon Kim, Gab-Su Seo, C. Chun, B. Cho, Seongjun Lee
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引用次数: 42

摘要

本研究研究了碳包覆LiFePO4电池的电特性,重点研究了其特定的开路电压(OCV)特性,包括在荷电状态(SOC)上非常平坦的OCV曲线和明显的滞后现象。通过对LiFePO4/C电池放电/充电OCV测量数据的研究,可以阐明这些现象。提出了一种简单的等效电路模型,并将其应用于扩展卡尔曼滤波(EKF)算法中基于OCV迟滞效应的SOC估计。将OCV与SOC之间的关系间隔降低到5% ΔSOC步,提高了算法的性能。此外,为了补偿由等效电路模型和参数变化引起的模型误差,由于模型精度在EKF算法中至关重要,为了获得良好的估计,实现了测量噪声模型和数据抑制。所提工作的所有SOC估算结果在±5%的范围内满足规范。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
OCV hysteresis effect-based SOC estimation in extended Kalman filter algorithm for a LiFePO4/C cell
This work investigates the electric characteristics of a carbon-coated LiFePO4 cell with emphasis on their specific open-circuit voltage (OCV) characteristics, which include very flat OCV curves over the state-of-charge (SOC) and pronounced hysteresis phenomena. Examining discharging/ charging OCV measurement data of a LiFePO4/C cell elucidates these phenomena. A simple equivalent circuit model is newly derived and used in an OCV hysteresis effect-based SOC estimation in the extended Kalman filter (EKF) algorithm. The interval of the relationship between the OCV and SOC is decreased to 5% ΔSOC steps to improve the performance of the algorithm. Additionally, to compensate the model errors caused by the equivalent circuit model and variation in parameters, a measurement noise model and data rejection are implemented because the model accuracy is critical in the EKF algorithm in order to obtain a good estimation. All SOC estimation results of the proposed work satisfy the specification within ±5%.
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