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Electrical Engineering and Systems Science > Systems and Control

arXiv:2201.02282 (eess)
[Submitted on 7 Jan 2022 ]

Title: Voltage-Based State of Charge Correction at Charge-End

Title: 基于电压的充电结束时的荷电状态修正

Authors:Ali Abdollahi, Jianwei Li, Xiaojun Li, Trevor Jones, Asif Habeebullah
Abstract: A voltage-based method is proposed to correct battery pack state of charge (SOC) estimation at the charge-end. Two main characteristics make the charge-end time span a good opportunity to correct SOC estimation: first, it is easy to detect when the battery is at the last stage of charging because the charging profile is known to the BMS designer and also during the charge-end time span the amount of current is low, and the terminal voltage of the battery cells are high; second, as the battery reaches the charge-end stage, we know that the true SOC is approaching to 100%. This paper presents a method to utilize these important features to correct the SOC estimation error. Using a voltage threshold method, the algorithm detects when the battery is close to the charge-end to activate the charge-end SOC correction strategy. Once activated, the strategy corrects the SOC using the maximum cell voltage to guarantee that SOC is 100% when charging is complete. The amount of correction is a function of maximum cell voltage and the charge current C-rate.
Abstract: 基于电压的方法被提出用于在充电结束时校正电池组的荷电状态(SOC)估计。 两个主要特性使得充电结束时间段成为校正SOC估计的良好时机:首先,在电池处于充电最后阶段时容易检测到,因为充电轮廓对BMS设计者是已知的,并且在充电结束时间段内电流量较低,电池单元的端电压较高;其次,当电池达到充电结束阶段时,我们知道真实SOC接近100%。 本文提出一种方法,利用这些重要特性来校正SOC估计误差。 使用电压阈值方法,该算法检测电池何时接近充电结束以激活充电结束SOC校正策略。 一旦激活,该策略使用最大单元电压来确保充电完成时SOC为100%。 校正的量是最大单元电压和充电电流C率的函数。
Subjects: Systems and Control (eess.SY)
Cite as: arXiv:2201.02282 [eess.SY]
  (or arXiv:2201.02282v1 [eess.SY] for this version)
  https://doi.org/10.48550/arXiv.2201.02282
arXiv-issued DOI via DataCite
Journal reference: 2021 IEEE Vehicle Power and Propulsion Conference (VPPC)
Related DOI: https://doi.org/10.1109/VPPC53923.2021.9699170
DOI(s) linking to related resources

Submission history

From: Xiaojun Li [view email]
[v1] Fri, 7 Jan 2022 01:19:25 UTC (678 KB)
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