Toyota Jidosha Kabushiki Kaisha

Kotaro Shibuya

Junta Izumi

Masahiko Mitsui

Juni Yasoshima

A trained neural network model is a neural network model which has been trained based on Nyquist plots of a plurality of modules of which full charge capacity is within a reference range. A processing system determines to which of a first group of modules of which full charge capacity is within the reference range and a second group of modules of which full charge capacity is out of the reference range a module belongs, based on discriminant analysis in which at least one feature value extracted from the Nyquist plot of the module is adopted as an explanatory variable. When the processing system determines that the module M belongs to the first group, the processing system estimates a full charge capacity of the module by using the trained neural network model.

Battery information processing system, method of estimating capacity of secondary battery, and battery assembly and method of manufacturing battery assembly

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Nagoya, Japan

Kotaro Shibuya