Abstract: 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.

Abstract: 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.

Abstract: A battery information processing system processes information for estimating a full charge capacity of a module. The battery information processing system includes a storage device configured to store a trained neural network model and an analysis device configured to estimate a full charge capacity of a secondary battery from a result of measurement of an AC impedance of the module by using the trained neural network model. The trained neural network model includes an input layer given a numeric value for each pixel of an estimation image in which a Nyquist plot representing the result of measurement of the AC impedance of the module is drawn in a region consisting of a predetermined number of pixels.