Secondary battery low-voltage defect determination system and secondary battery defect determination method using the same

1 . A secondary battery low-voltage defect determination system, comprising:

a database configured to store existing data on battery manufacturing process conditions, activation process conditions, voltage measurement conditions, and a battery voltage measured after an activation process of a battery;

a detector configured to detect experimental data on the battery manufacturing process conditions, the activation process conditions, the voltage measurement conditions, and the battery voltage measured after the activation process of the battery;

a calculator configured to calculate target voltage drop correction data based on the existing data stored in the database and the experimental data detected by the detector; and

a determinator configured to determine whether the battery has a defect by comparing the target voltage drop correction data and a reference voltage drop data of a normal battery,

wherein the target voltage drop correction data is based on applying a micro-current in a constant current mode, and measuring an amount of change in voltage while initiating self-discharge for a set period when a charging voltage reaches a target voltage.

2 . The secondary battery low-voltage defect determination system of claim 1 , wherein the existing data stored in the database and the experimental data detected by the detector include one or more of:

a battery size, an electrolyte injection amount, a type of active material, an electrode loading amount, a negative/positive (N/P) ratio, an aging temperature, an aging time, an aging frequency, a charge/discharge temperature, a charge/discharge capacity, a charge/discharge frequency, a charge/discharge time, an electrolyte discharge amount, a voltage measurement waiting time, a measurement voltage/current mode, a measured voltage, and a measured voltage drop.

3 . The secondary battery low-voltage defect determination system of claim 2 , wherein the measured voltage drop is measured during a self-discharge period.

4 . The secondary battery low-voltage defect determination system of claim 3 , wherein the self-discharge period is approximately 24 hours.

5 . The secondary battery low-voltage defect determination system of claim 1 , wherein the database defines a correlation equation through a correlation analysis between the existing data and the target voltage drop correction data.

6 . The secondary battery low-voltage defect determination system of claim 5 , wherein the correlation analysis is a regression analysis with the existing data as an independent variable and the target voltage drop correction data as a dependent variable.

7 . The secondary battery low-voltage defect determination system of claim 5 , wherein the calculator calculates the target voltage drop correction data by substituting the experimental data detected by the detector as an independent variable into the correlation equation.

8 . The secondary battery low-voltage defect determination system of claim 5 , wherein a number of batteries serving as a population for the correlation analysis is from about 1,000 to 30,000.

9 . The secondary battery low-voltage defect determination system of claim 1 , wherein the defect to be determined is a low-voltage defect.

10 . A secondary battery low-voltage defect determination method using a secondary battery low-voltage defect determination system, the secondary battery low-voltage defect determination method comprising:

storing, in a database, existing data on battery manufacturing process conditions, activation process conditions, voltage measurement conditions after an activation process, and a measured battery voltage of a battery;

detecting, by a detector, experimental data on the battery manufacturing process conditions, the activation process conditions, the voltage measurement conditions after the activation process, and the measured battery voltage of the battery;

calculating, by a calculator, a corrected voltage drop based on the stored existing data and the detected experimental data; and

determining, by a determinator, whether the battery has a defect by comparing the corrected voltage drop and a reference voltage drop of a normal battery after the calculating the corrected voltage drop,

wherein the corrected voltage drop is based on applying a micro-current in a constant current mode, and measuring an amount of change in voltage while initiating self-discharge for a set period when a charging voltage reaches a target voltage.

11 . The secondary battery low-voltage defect determination method of claim 10 , wherein the stored existing data and the detected experimental data includes one or more of:

a battery size, an electrolyte injection amount, a type of active material, an electrode loading amount, a negative/positive (N/P) ratio, an aging temperature, an aging time, an aging frequency, a charge/discharge temperature, a charge/discharge capacity, a charge/discharge frequency, an electrolyte discharge amount, a voltage measurement waiting time, a measurement voltage/current mode, a measured voltage, and a measured voltage drop.

12 . The secondary battery low-voltage defect determination method of claim 10 , wherein the storing the existing data comprises:

determining an independent variable and a dependent variable among the existing data; and

defining a correlation equation for analyzing a correlation between the independent variable and the dependent variable through a correlation analysis.

13 . The secondary battery low-voltage defect determination method of claim 12 , wherein the correlation analysis is a regression analysis with the existing data as the independent variable and a target voltage drop correction data as the dependent variable.

14 . The secondary battery low-voltage defect determination method of claim 12 , wherein the calculating the corrected voltage drop comprises:

substituting the detected experimental data as the independent variable of the correlation equation; and

calculating a target voltage drop correction data, which is the dependent variable, by the correlation equation.