A novel dual-scale cell state-of-charge estimation approach for series-connected battery pack used in electric vehicles
A novel dual-scale cell state-of-charge estimation approach for series-connected battery pack used in electric vehicles
复制标题
一种用于电动汽车串联电池组的新型双尺度电池充电状态估计方法
DOI：
10.1016/j.jpowsour.2014.10.119
复制
发表时间：
2015-01-15
影响因子：
9.2
通讯作者：
Xiong, Rui
中科院分区：
文献类型：
--
作者：
Sun, Fengchun;Xiong, Rui
由于串联电池组的不一致性，准确估计电池的荷电状态仍然是一个挑战。本文试图做出三点贡献。(1)提出了一种参数化建模方法，用于开发基于模型的SoC估计方法。在分析电池参数与其SoC之间映射关系的基础上，提出了一种三维响应面开路电压模型，用于校正错误的SoC估计。(2)提出了一种考虑模型和参数不确定性的改进电池模型，用于对电池组中的多个电池进行建模。提出了一种筛选具有电池组“平均容量”和“平均电阻”的电池的方法，以建立电池组的标称模型。为了提高电池标称模型的可扩展性，提出了一种基于平均电池模型的单电池偏差校正方法。(3)提出了一种新的基于模型的双尺度单元SoC估计器。它使用微观和宏观的时间尺度来估计的SoC的选定的细胞和SoC的细胞分别。最后，所提出的方法已经通过两个锂离子电池组进行了验证。结果表明，对于不确定的潜水周期和电池组，电池电压和SoC的最大估计误差分别小于30 mV和1%。(C)2014爱思唯尔有限公司版权所有。
Accurate estimations of cell state-of-charge for series-connected battery pack are remaining challenge due to the inhabited inconsistency characteristic. This paper tries to make three contributions. (1) A parametric modeling method is proposed for developing model-based SoC estimation approach. Based on the analysis for the mapping relationship between battery parameters and its SoC, a three-dimensional response surface open circuit voltage model is proposed for correcting erroneous SoC estimation. (2) An improved battery model considering model and parameter uncertainties is developed for modeling multiple cells in battery pack. A filtering process for selecting cell having "average capacity" and "average resistance" of battery pack has been developed to build the nominal battery model. Then a bias correction for single cells based on an average cell model is proposed for improving the expansibility of the nominal battery model. (3) A novel model-based dual-scale cell SoC estimator has been proposed. It uses micro and macro time scale to estimate the SoC of the selected cell and unselected cells respectively. Lastly, the proposed approach has been verified by two lithium-ion battery packs. The results show that the maximum estimation errors for cell voltage and SoC are less than 30 mV and 1% respectively against uncertain diving cycles and battery packs. (C) 2014 Elsevier B.V. All rights reserved.