The invention relates to the technical field of battery analysis, in particular to a battery state prediction method and device, computer equipment and a storage medium. The method comprises the steps of determining battery state parameters corresponding to a target vehicle according to initial battery parameters of the target vehicle; inputting the battery state parameters into a pre-trained target neural network model to obtain a relative error and an average error output by the target neural network model; wherein the target neural network model is obtained by training according to an initial sample parameter of the target vehicle, a vehicle internal parameter of the target vehicle and a vehicle use environment; and determining the vehicle battery state of the target vehicle according to the relative error and the average error. The method guarantees the prediction accuracy of the vehicle battery state, and guarantees that the vehicle battery state can accurately reflect the actual condition of the vehicle battery.
本申请涉及电池分析技术领域,特别是涉及一种电池状态预测方法、装置、计算机设备和存储介质。方法包括:根据目标车辆的初始电池参数,确定目标车辆对应的电池状态参数;将电池状态参数输入至预先训练的目标神经网络模型,得到目标神经网络模型输出的相对误差和均分误差;其中,目标神经网络模型是根据目标车辆的初始样本参数,以及目标车辆的车辆内部参数和车辆使用环境训练得到;根据相对误差和均分误差,确定目标车辆的车辆电池状态。本申请保证了车辆电池状态的预测准确性,保证了车辆电池状态能够准确反映车辆电池的实际情况。
Battery state prediction method and device, computer equipment and storage medium
电池状态预测方法、装置、计算机设备和存储介质
08.10.2024
Patent
Elektronische Ressource
Chinesisch
IPC: | G01R Messen elektrischer Größen , MEASURING ELECTRIC VARIABLES / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / B60L PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES , Antrieb von elektrisch angetriebenen Fahrzeugen / G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung |
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