# A Data-Driven Battery Degradation Estimation Method for Low-Earth-Orbit (LEO) Satellites
## 2 Background on LEO Satellite Power System and Methods
### LEO Satellite System Characteristics  
Continuous monitoring or prediction of the battery's status is essential for the LEO satellite mission's design and system state assessment [17]. However, the estimation of battery aging over a satellite's operational lifespan is often overlooked or conducted based on user-defined empirical criteria [18]. Among the methods developed for this purpose are direct current internal resistance (DCIR) techniques, which involve assuming specific mission scenarios for the battery. However, DCIR requires the analysis to be performed under identical conditions, requiring users to manually interpret satellite data trends and select voltage and current profiles that match these conditions. Additionally, satellite-stored data can be subject to errors caused by radiation effects, and constraints on data transmission and storage may lead to insufficient sampling intervals for certain data points [19]. These challenges make the development of reliable aging prediction technologies critical for satellite mission planning, operational assessment, and the identification of a satellite's nominal functionality. However, addressing these challenges requires overcoming significant technical and analytical difficulties. First, the characteristics of the telemetry data used for state estimation in LEO satellites are summarized. The transmission interval of telemetry data packets is determined based on the satellite's operational state and the rate of data changes. Data that exhibit rapid variations and require real-time monitoring must be transmitted at short intervals. These short intervals enable the early detection of anomalies and facilitate prompt responses. Conversely, data with slower changes or lower importance can be transmitted at longer intervals. Bit allocation for telemetry data packets is determined according to the importance of the data items and the accuracy requirements for transmission. For instance, power system data are essential for satellite operations and require high accuracy. Similarly, attitude control system data are given priority in bit allocation because of the precision required to maintain the satellite's orbit and attitude stability. However, limitations in bandwidth impose constraints on data accuracy and transmission intervals, necessitating careful consideration of these factors to optimize the performance of telemetry systems. Figure 2: Transformer network diagram. In this study, we developed a data-driven model for battery voltage modeling and assessed its application to aging modeling. During this process, telemetry data from on-orbit satellites can be affected by single-event upsets (SEUs) caused by radiation, leading to the generation of outliers, as shown in Figure 3. Additionally, satellite data are typically stored in the onboard memory at varying intervals for subsequent transmission to the ground, which can result in data from the same time point not being consistently generated. In LEO satellites, the data collected are recorded at specific intervals, considering transmission and storage capacity limitations. In medium-to-large-scale LEO satellites, such as KOMPSAT-5, telemetry systems are redundantly designed with multiple sensors to account for potential failures, as illustrated in Figure 4. As a result, even for the same voltage, sensor readings at the same time point may exhibit variations owing to differing noise levels and offsets. All sensor readings must be utilized to enhance the resolution of the features for training and a filtering process must be applied. In this study, the sensor data were aggregated, offset errors were corrected, and a filtering process was employed to eliminate high-frequency noise. This preprocessing step ensured the data had the quality required for the accurate and reliable modeling of satellite battery behavior and performance. LEO satellites operate with limited power resources and ground contact duration; thus, they must make accurate battery state predictions, which is essential for effective mission planning.