基于云端放电数据的电池组一致性研究

为提升电池组放电数据使用价值,减少对电池组充电数据的依赖,改变放电数据因质量差、采集效率低等原因难以得到有效利用的现状,以云端放电数据为研究对象,提出一种动力电池组一致性评价方法。该方法筛选出电池组的有效放电循环数据片段,根据每一放电循环中的单体电压曲线绘制包络线,进而基于上下各数条包络线进行数学计算,最终拟合得到一条一次曲线,根据最终拟合一次曲线斜率大小对一致性进行定量评价。试验结果表明,对于不同一致性状况的电池组,该方法能合理对其评分;实车数据分析表明,该方法能有效运用于工程中。该方法为电池组一致性的评价提供一种新思路,在一定程度上实现放电数据的有效利用价值。

Research on Battery Pack Consistency Based on Cloud Discharge Data

In order to improve the usage of battery pack discharge data and reduce the dependence on charging data, a consistency evaluation method for power battery packs is proposed based on the cloud discharge data. Initially the effective segments of the discharge cycle data were chosen, and the envelope curves were drawn according to the single cell voltage curve in each discharge cycle. The upper and lower envelope curves were fitted mathematically using the first-order curve fitting. The consistency was quantitatively estimated based on the slope of the first-order curves. The experimental results show that the proposed method can reasonably evaluate the batteries with different consistency and can be effectively applied in the analysis of real vehicle data. This method provides a new idea for the evaluation of battery consistency and improves the utilization of discharge data to a certain extent.