# Lithium-Ion Battery Capacity Prediction with GA-Optimized CNN, RNN, and BP
## 2 Overview and Dataset Information
### Feature Extraction and Selection  
Voltage and current measurements during the charging and discharging cycles of the batteries were used to predict the battery capacity.  
During ChargingThe first stage of charging is constant current (CC), followed by the second stage of constant voltage (CV). The duration of the CC and CV stages varies depending on the capacity and number of cycles of the battery. Therefore, based on the current measured during charging, the time during which the current remains constant is determined as the first characteristic. In the current-time graph during charging, shown for the B0005 battery in Figure 4a, the duration of constant current is arranged from smallest to largest for the 75 th, 50 th, and 25 th cycles. It is predicted that this duration of constant current will decrease as the number of cycles increases. The duration of constant voltage is also determined as the second feature. As shown in Figure 4b, for the B0005 battery during charging, the duration of constant voltage was arranged from smallest to largest for the 25 th, 50 th, and 75 th cycles. With an increase in the number of cycles, it is expected that the duration of constant voltage will also increase.  
During DischargingTwo important features were derived from the battery discharge measurements conducted by NASA during the discharge process. The average voltage measured during a cycle varies depending on the number of cycles. As clearly seen in Figure 5, the average voltage decreases with an increase in the number of cycles. Therefore, the average voltage was determined as the third characteristic. Additionally, the point at which the lowest level is reached in the measured voltages varies depending on the number of cycles and, consequently, the battery's capacity. It is observed that the lowest voltage is reached at the 75 th, 50 th, and 25 th cycles, respectively. As the number of cycles increases, the duration of this lowest voltage moment is predicted to decrease. The moment of the lowest measured voltage was identified as the fourth determining feature.  
Since the other battery characteristics and voltage-current charts exhibit similar trends, it is considered sufficient to present only the feature extraction from the B0005 battery. These four features were extracted from all four different batteries in the NASA dataset. The linear relationship between the two independent variables--direction and strength--was determined using the correlation coefficient. The correlation coefficients of the extracted features with the target battery capacities are shown in Table 1. Here, HFs represent feature numbers: For the features during charging, HF1 is constant current time and HF2 is constant voltage time. For the features during discharge, HF3 is the average voltage and HF4 is the moment when the measured voltage is lowest. It is observed that the four features extracted  
Figure 4: The charts during charging: (**a**) current–time chart; (**b**) voltage–time chart.  
from batteries B0005 and B0006 have high correlation coefficients. Therefore, these four features were used for capacity prediction in these batteries. However, the correlation coefficient of HF2 in B0007 and HF1 in B0018 is low. Therefore, HF1, HF3, and HF4 for battery B0007 and HF2, HF3, and HF4 for battery B0018 were used for capacity prediction.