The invention discloses a battery life prediction method and device, electronic equipment and a storage medium, and relates to the technical field of battery management, and the method comprises the steps: determining an initial training model; wherein the initial training model is a training model determined through transfer learning; acquiring target battery parameters of a vehicle battery; wherein the target battery parameters comprise battery voltage, battery current, battery temperature and cycle index; determining an initial battery life according to the battery voltage, the battery current, the battery temperature, the cycle index and the initial training model; and predicting the battery life according to the initial battery life and the battery life prediction model, and determining the target battery life. According to the technical scheme of the invention, based on fusion of the initial training model, data driving of transfer learning and the battery life prediction model, the residual service life of the lithium battery can be accurately estimated in the absence of a training data set, the accuracy of life estimation is improved, and the user experience is improved.
本发明公开了一种电池寿命的预测方法、装置、电子设备和存储介质,涉及电池管理技术领域,该方法包括:确定初始训练模型;其中,初始训练模型为通过迁移学习确定的训练模型;获取车辆电池的目标电池参数;其中,目标电池参数包括电池电压、电池电流、电池温度和循环次数;根据电池电压、电池电流、电池温度、循环次数和初始训练模型确定初始电池寿命;根据初始电池寿命和电池寿命预测模型进行电池寿命的预测,确定目标电池寿命。本发明的技术方案,基于初始训练模型、迁移学习的数据驱动和电池寿命预测模型相融合,实现面对在缺少训练数据集的情况下也能锂电池的剩余使用寿命进行准确估计,提高寿命估计的准确性,提升用户使用体验感。
Battery life prediction method and device, electronic equipment and storage medium
一种电池寿命的预测方法、装置、电子设备和存储介质
2024-04-19
Patent
Electronic Resource
Chinese
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