The invention discloses a lithium battery state-of-charge estimation system and method with fast migration capability. The system comprises a data measurement module, a neural network training module, a network updating module and a state evaluation module. The data acquisition module is used for acquiring historical data of the lithium battery, and the historical data comprises historical voltage data, historical current data, historical temperature data and historical charge state data; the neural network training module is used for constructing an initial state evaluation network and training the initial state evaluation network based on historical data to obtain a state evaluation network; the network updating module is used for measuring real-time data of the lithium battery and updating parameters of the state evaluation network based on the real-time data of the lithium battery to obtain an updated state evaluation network, and the real-time data of the lithium battery comprises real-time voltage data, real-time current data and real-time temperature data; and the state evaluation module is used for performing state evaluation based on the updated state evaluation network and the lithium battery real-time data to obtain an evaluation result.
本发明公开了具备快速迁移能力的锂电池荷电状态估计系统及方法,系统包括:数据测量模块、神经网络训练模块、网络更新模块和状态评估模块;数据采集模块用于采集锂电池的历史数据,历史数据包括:历史电压数据、历史电流数据、历史温度数据和历史荷电状态数据;神经网络训练模块用于构建初始状态评估网络,并基于历史数据对初始状态评估网络进行训练,得到状态评估网络;网络更新模块用于测量锂电池实时数据,并基于锂电池实时数据对状态评估网络的参数进行更新,得到更新后状态评估网络,锂电池实时数据包括:实时电压数据、实时电流数据和实时温度数据;状态评估模块用于基于更新后状态评估网络和锂电池实时数据进行状态评估,得到评估结果。
Lithium battery state-of-charge estimation system and method with rapid migration capability
具备快速迁移能力的锂电池荷电状态估计系统及方法
2024-06-18
Patent
Electronic Resource
Chinese
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