# CubeSat Mission Scheduling Method Considering Operational Reliability
## 5 Case Study
### Optimization Result Analysis  
Applying the previously established scheduling framework, on the basis of meeting mission requirements and maintaining battery life, we must determine when the payload of the 3U CubeSat can be activated and obtain the optimal scheduling scheme for the CubeSat on a minute-by-minute basis. In order to verify the effectiveness of the scheduling method, for the following three different scheduling schemes, the MIP model is solved by the BB method, and the CubeSat power situation, task scheduling results, and start-up design results are compared and analyzed. The scheduling results are shown in Figure 2, and the energy analysis is shown in Figure 3. Tables 8 and 9 give the comparison of the running results. The specific scheduling results of the three schemes are shown in Figure 2. Since task I is a core module with the highest priority, it is eligible to be invoked preferentially during the entire scheduling time and will work continuously without interruption throughout the entire time period. Payload A will be constrained by the time window and will only be executed within its time window (31-80 min). The same is true for payloads E and F. The time distribution of the rest of the payloads also follows the task execution constraints mentioned in Section 4.3.1 above. From the comparison results in Table 8, it can be seen that the initial start of the task of Scheme 1 is not subject to any constraints, and multiple payloads start at the same time during \(t=1\) min, which may generate a large surge current and lower the bus voltage. Moreover, the start-up sequence of the payload does not follow certain rules and is in a disorderly start-up mode. \"Disorder\" includes two situations: on the one hand, multiple payloads are started at the same time when powered on, which will lead to a large impulse current at the start of the instant, affecting the service life of electronic equipment, reducing the reliability of key components, and even pulling down the bus voltage, resulting in unexpected power shutdown; on the other hand, the power-on sequence of multiple payloads is chaotic and does not follow the priority relationship. Some devices may start to work before initialization, resulting in system instability or data loss. Therefore, it is necessary to plan the start-up priorities properly and first power on payloads with higher start-up priorities. Under this scheduling scheme, the start-up process of the CubeSat may fail or enter a permanent power-off state, so it is not advisable. Scheme 2 realizes the step-by-step start-up design through optimized scheduling, avoids the simultaneous start-up of multiple payloads, and improves the reliability and success rate of the CubeSat start-up. Except payloads A and F, which have specific time windows, the initial start-up of other tasks follows the order of priority. The energy scheduling results are shown in Figure 3. The CubeSat is in the light area during 1-32 min and 70-100 min. At this time, the PV input provides energy for the CubeSat load mission and charges the battery at the same time; however, CubeSats orbit in space in sun-synchronous orbits around the Earth. When the CubeSat orbits to the back of the Earth, the Earth will block the sun's rays, and the CubeSat is in the shadow zone. The PV panels have no power output, and the input power is not enough to provide energy for the mission during certain periods (e.g., 76-77 min). At this time, the lithium battery and PV input together provide energy for the mission. The CubeSat is in the shadow area at 33-69 min, and the PV input power is 0. At this time, the battery alone is used to provide energy for the payload. It can be seen from the comparison results in Table 9 that Scheme 2 only considers the maximization of task value. Under this scheduling scheme, the relevant reliability