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Deterioration estimation device, model generation device, deterioration estimation method, model generation method, and program

机译:劣化估计设备,模型生成装置,劣化估计方法,模型生成方法和程序

摘要

PROBLEM TO BE SOLVED: To estimate future SOH of a storage battery with high accuracy. A deterioration estimation device 20 includes a storage processing unit 210 and a calculation unit 240. The storage processing unit 210 acquires a plurality of models from the model generation device 10 and stores them in the model storage unit 220. In these plurality of models, the number of charge / discharge is β (where β> αj) with the training measurement data showing the result of measuring the state of the storage battery when the number of charge / discharge is from αi to αj (where j ≧ i) as an input value. ), It is generated by machine learning the training data with SOH as the target value indicating the deterioration state of the storage battery. The calculation unit 240 calculates the estimation result of the transition of the SOH of the storage battery 30 managed by the deterioration estimation device 20 by using a plurality of models in which the model storage unit 220 is stored. [Selection diagram] Fig. 3
机译:要解决的问题:以高精度估计蓄电池的未来SOH。劣化估计设备20包括存储处理单元210和计算单元240.存储处理单元210从模型生成设备10获取多个模型,并将它们存储在模型存储单元220中。在这些多个模型中,充电/放电的数量是β(其中β>αj),训练测量数据显示当充电/放电的数量从αi到αj(其中j≠i)作为输入时测量蓄电池状态的结果价值。 ),它是由机器学习用SOH的训练数据生成的,作为指示蓄电池的劣化状态的目标值。计算单元240通过使用存储模型存储单元220的多个模型来计算由劣化估计设备20管理的存储电池30的SOH的转换的估计结果。 [选择图]图3

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