The invention discloses a battery SOC estimation method and device and a medium, and the method comprises the steps: carrying out the normalization processing of a battery SOC related data set, and eliminating the dimension difference of the current and voltage related characteristics of a battery; dividing the data set into a training set and a test set, performing preliminary prediction on internal rules of battery SOC related factors by sequentially using a primary prediction model (ExrRa Tres, LightGBM, TSVR) through a K-fold cross validation method, fusing prediction results of a verification set and a test set of K sub-models of the primary prediction model by using a weight scaling strategy, and performing prediction on the prediction results of the verification set and the test set of the K sub-models of the primary prediction model; and the new features are respectively added to a new training set and a new test set, and are used as the input of the secondary prediction model to obtain a final prediction result, so that the SOC estimation precision of the battery is improved.
本发明公开一种电池SOC估计方法、设备及介质,首先,对电池SOC相关数据集进行归一化处理,消除电池的电流和电压相关特征的量纲差异;接着将数据集划分为训练集和测试集,依次使用一级预测模型(ExrRa Trees、LightGBM、TSVR)通过K折交叉验证方法对电池SOC相关因素的内在规律进行初步预测,对一级预测模型的K个子模型的验证集和测试集预测结果使用权重缩放策略进行融合,作为新特征分别添加到新的训练集和测试集,作为二级预测模型的输入以得到最终预测结果,提高了电池SOC估计精度。
Battery SOC (State of Charge) estimation method, equipment and medium
一种电池SOC估计方法、设备及介质
2023-11-10
Patent
Electronic Resource
Chinese
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