Abstract: A prediction system includes a charger and an estimation apparatus, and performs a method of predicting capacity degradation of a secondary battery. The estimation apparatus obtains changes of a plurality of parameters of capacity degradation, based on a fitting operation of fitting, to a target-battery charge curve of a target battery, reference data of the target battery or a battery of the same type as the target battery. Further, the estimation apparatus identifies a degradation change point where the degradation speed of the maximum battery capacity becomes high as a result of increase of the usage degree of the target battery, based on the plurality of obtained parameters.

Abstract: The method for producing a solid electrolyte sheet according to the present invention comprises: a first step of applying a first slurry containing a solid electrolyte to a substrate to form a first uncured product; a second step of drying the first uncured product on the substrate to form a first solid electrolyte layer; a third step of applying a second slurry to an upper surface of the first solid electrolyte layer to form a second uncured product; a fourth step of digging a sheet-formed three-dimensional structure into the second uncured product; and a fifth step of drying the second uncured product that has entered inside the three-dimensional structure and the second uncured product that is present on the three-dimensional structure to form a second solid electrolyte layer inside and on the three-dimensional structure, thereby obtaining a solid electrolyte sheet with the second solid electrolyte layer filling inside of the three-dimensional structure.

Abstract: In a method of estimating an internal degradation state of a degraded cell, a measurement system calculates a target capacity characteristic curve by differentiating current capacity by voltage on a target charge curve of a target battery. Further, the method obtains changes of parameters of different types based on a fitting operation that fits the curve and a reference capacity characteristic curve calculated from reference data. In the fitting operation, whichever of low current capacity regions and high current capacity regions of the curve and the curve have a stronger correlation are fit first and whichever of them have a weaker correlation are fit later.

Abstract: What are provided are a positive electrode for a lithium-ion battery capable of suppressing the generation of carbon dioxide while increasing the battery capacity of the lithium-ion battery, a lithium-ion battery and a method for producing a positive electrode for a lithium-ion battery. A positive electrode for a lithium-ion battery having a positive electrode current collector and a positive electrode active material layer, in which the positive electrode active material layer has a positive electrode mixture containing the positive electrode active material, and the positive electrode mixture contains lithium carbonate in a range of 9% by mass or more and 20% by mass or less with respect of the total weight thereof.

Abstract: A recovery processing method of a lithium ion battery includes repeating a cycle a plurality of times, and the cycle includes a first process of setting an SOC of the lithium ion battery to a first value that is equal to or less than a value of the SOC where a gradient of an SOC-voltage curve is a minimum value through charging, and a second process of setting the SOC of the lithium ion battery to a second value smaller than the first value through discharging.

Abstract: A recovery processing method of a lithium ion battery of an embodiment is a processing method of recovering performance of the lithium ion battery. The recovery processing method of the lithium ion battery includes a process of holding an SOC of the lithium ion battery at a fixed value that is within a range of 10% to 70%. The SOC in the process is preferably set to equal to or smaller than a value in which a gradient of an SOC-voltage curve has a minimum value.

Abstract: A recovery processing method of a lithium ion battery having a positive electrode and a negative electrode and in which performance has decreased due to a residue of lithium ions in the negative electrode, the method comprises: repeating a cycle a plurality of times, the cycle including: a first process of setting an SOC of the lithium ion battery to a first value, that is equal to or smaller than a value of the SOC in which a gradient of an SOC-voltage curve is a minimum value and that is equal to or greater than the value of the SOC in which the gradient of the SOC-voltage curve is two times the minimum value, by charging; and a second process of setting the SOC of the lithium ion battery to a second value, that is smaller than the first value, by discharging.

Abstract: A battery model construction method is a method for constructing a battery model that treats powers of a plurality of usage history parameters defined on a basis of time series data about a current, a voltage, and a temperature of a battery as explanatory variables and treats a predicted SOH value as an objective variable, the method including: an acquiring step ST1 for acquiring time series data of usage history parameters and measured SOH values; an exponentiating step ST2 for raising the usage history parameters by a prescribed exponent to thereby generate time series data of input parameters; a training step ST4 for training the battery model by using the time series data of the input parameters and the measured SOH values as training data; and a searching step ST8 for searching for an optimal exponent by repeatedly performing the steps ST2 and ST4 while varying the exponent.

Abstract: A battery model construction method includes: a step ST2 for constructing a battery model; steps ST3 and ST4 for evaluating, for each sample battery, the prediction error between a measured value of the SOH and a predicted value according to the battery model, and determining whether there is inherent bias in the prediction error for each sample battery; steps ST5 and ST6 for constructing a first error prediction model associating explanatory variables defined on the basis of usage history parameters with an objective variable, and determining whether a first correlation exists between the measured value of the average prediction error acquired in steps ST3 and ST4 and the predicted value according to the first error prediction model; and a step ST7 for reconstructing the battery model in the case where it is determined that there is bias and that the first correlation exists in steps ST5 and ST6.

Abstract: A data abnormality determination apparatus 1 determines that there is an abnormality in input data and is provided with: a probability density calculator 11 that calculates, as an input density value, a probability density value for the input data in a probability density function constructed based on a data set; an occurrence probability calculator 12 that calculates, as an occurrence probability with respect to the input data, a value corresponding to an integral of the probability density function across a tail region in which the probability density value in the probability density function is equal to or less than the input density value; and an abnormality determiner 13 determines that there is an abnormality in the input data based on the occurrence probability.

Abstract: A prediction system includes a charger and an estimation apparatus, and performs a method of predicting capacity degradation of a secondary battery. The estimation apparatus obtains changes of a plurality of parameters of capacity degradation, based on a fitting operation of fitting, to a target-battery charge curve of a target battery, reference data of the target battery or a battery of the same type as the target battery. Further, the estimation apparatus identifies a degradation change point where the degradation speed of the maximum battery capacity becomes high as a result of increase of the usage degree of the target battery, based on the plurality of obtained parameters.

Abstract: In a method of estimating an internal degradation state of a degraded cell, a measurement system calculates a target capacity characteristic curve by differentiating current capacity by voltage on a target charge curve of a target battery. Further, the method obtains changes of parameters of different types based on a fitting operation that fits the curve and a reference capacity characteristic curve calculated from reference data. In the fitting operation, whichever of low current capacity regions and high current capacity regions of the curve and the curve have a stronger correlation are fit first and whichever of them have a weaker correlation are fit later.

Abstract: A measurement system has a charger and an estimation apparatus and performs a method of estimating the internal degradation state of a degraded cell. The estimation apparatus calculates a reference capacity characteristic curve by differentiating a reference charge curve, sets a reference capacity characteristic curve, which is less than a division point, to a negative electrode characteristic curve, and sets a reference capacity characteristic curve, which is not less than the divisional point, to a positive electrode characteristic curve. Further, the estimation apparatus calculates a target capacity characteristic curve by differentiating the target charge curve and fits the target capacity characteristic curve and each of the negative electrode characteristic curve and the positive electrode characteristic curve, thereby obtaining changes of a plurality of types of parameters.