Analyzing device, predicting device, analyzing method, predicting method, and program

A predicting device comprising:

• a processor;
• and
• a memory storing program instructions that cause the processor to:
• calculate, by factoring a relationship between a voltage and a current capacity calculated from cycle measurement data of a target battery up to a predetermined cycle, factor intensity transition data indicating a change up to the predetermined cycle in intensity of each factor affecting the current capacity;
• generate a feature from the factor intensity transition data of each factor;
• and
• predict a lifetime characteristic of the target battery by inputting the generated feature into a model that has learned a relationship between a feature of each factor and lifetime data that are generated based on cycle measurement data for training up to the predetermined cycle.

An analyzing method performed by a computer, comprising:

• acquiring lifetime data from cycle measurement data of a target battery;
• calculating, by factoring a relationship between a voltage and a current capacity calculated from the cycle measurement data of the target battery, factor intensity transition data indicating a change in intensity of each factor affecting the current capacity and factor data representing a relationship between a voltage and a current capacity of each factor;
• and
• outputting the lifetime data, the factor data, and the factor intensity transition data.

A predicting method performed by a computer, comprising:

• calculating, by factoring a relationship between a voltage and a current capacity calculated from cycle measurement data of a target battery up to a predetermined cycle, factor intensity transition data indicating a change up to the predetermined cycle in intensity of each factor affecting the current capacity;
• generating a feature from the factor intensity transition data of each factor;
• and
• predicting a lifetime characteristic of the target battery by inputting the generated feature into a model that has learned a relationship between a feature of each factor and lifetime data that are generated based on cycle measurement data for training up to the predetermined cycle.

A non-transitory computer-readable storage medium having stored therein a program for causing a computer to perform:

• acquiring lifetime data from cycle measurement data of a target battery;
• calculating, by factoring a relationship between a voltage and a current capacity calculated from the cycle measurement data of the target battery, factor intensity transition data indicating a change in intensity of each factor affecting the current capacity and factor data representing a relationship between a voltage and a current capacity of each factor;
• and
• outputting the lifetime data, the factor data, and the factor intensity transition data.

A non-transitory computer-readable storage medium having stored therein a program for causing a computer to perform:

• calculating, by factoring a relationship between a voltage and a current capacity calculated from cycle measurement data of a target battery up to a predetermined cycle, factor intensity transition data indicating a change up to the predetermined cycle in intensity of each factor affecting the current capacity;
• generating a feature from the factor intensity transition data of each factor;
• and
• predicting a lifetime characteristic of the target battery by inputting the generated feature into a model that has learned a relationship between a feature of each factor and lifetime data that are generated based on cycle measurement data for training up to the predetermined cycle.