The embodiment of the invention provides a battery state-of-charge value determination method and device, a medium and a vehicle, and the method comprises the steps: obtaining at least one working state parameter sequence of a target battery at a first moment, the working state parameter sequence being used for describing the change condition of the working state parameter of the target battery along with time, the working state parameter sequence comprises a working state parameter value of the target battery at the first moment; determining target characteristic data of the target battery based on the at least one working state parameter sequence; and inputting the target feature data into a state-of-charge value prediction model, so that the state-of-charge value prediction model outputs a target state-of-charge value of the target battery at the first moment, the state-of-charge value prediction model being obtained by pre-training based on a bidirectional long-short term memory network. According to the technical scheme, the state-of-charge value of the battery is predicted based on the bidirectional long-short-term memory network, and the accurate state-of-charge value can be predicted under the condition of few computing resources.
本申请的实施例提供了一种电池荷电状态值的确定方法、装置、介质及车辆,包括:在第一时刻获取目标电池的至少一种工作状态参数序列,工作状态参数序列用于描述目标电池的工作状态参数随时间的变化情况,工作状态参数序列包括目标电池在第一时刻的工作状态参数值;基于至少一种工作状态参数序列,确定目标电池的目标特征数据;将目标特征数据输入至荷电状态值预测模型,以由荷电状态值预测模型输出目标电池在第一时刻的目标荷电状态值,荷电状态值预测模型是基于双向长短时记忆网络预先训练得到的。本申请的技术方案基于双向长短时记忆网络预测电池的荷电状态值,能实现在较少计算资源的条件下,预测出准确的荷电状态值。
Battery charge state value determination method and device, medium and vehicle
电池荷电状态值的确定方法、装置、介质及车辆
2024-09-03
Patent
Electronic Resource
Chinese
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