Simulation And State Prediction Of Micro-nano Satellite Power System Based On Multi-physical Quantity Coupling

Micro-nano-satellite is an important direction of aerospace development.Its power supply subsystem involves the mutual coupling of multiple physical quantities such as photoelectricity and heat.The complexity and uncertainty of performance make experimental verification very difficult.In this study,aiming at the performance evaluation of the micro-nano satellite power supply subsystem in orbit,a relationship model including the coupling of physical quantities such as motion,light,electric energy,and heat flow is established,and simulations are performed to analyze the state under different working conditions and discuss the performance degradation of solar cells and batteries.Impact on power performance.For satellites in the late stage of life in orbit,the performance change of the power supply subsystem is analyzed,and the state analysis is carried out using fuzzy reasoning.And based on neural networks,predict the important indicators of solar cell output power and battery capacity in the power supply subsystem.The research content of this paper includes the following three aspects:(1)Multi-physical quantity coupling analysis of micro-nano-satellite power supply subsystem.Aiming at the influence of motion,light,electric energy,heat flow and other factors on the satellite power supply subsystem in orbit,a multi-physical quantity coupling relationship model is established,and the interaction and coupling mechanism between multiple physical quantities are analyzed,and modeling and simulation are carried out to simulate different conditions.The performance of the satellite power subsystem.(2)Analysis of the impact of solar cell and battery parameter attenuation on the performance of the power subsystem.When the satellite power solar cell array is in orbit,it will be irradiated by high-energy particles such as the sun and cosmic radiation,and its performance will be attenuated,resulting in a decrease in output power;the capacity of the battery will continue to decrease as the number of charge and discharge increases.Performance evaluation of power subsystems using fuzzy inference for longterm on-orbit satellites at the end of their lifetime.(3)Prediction of solar battery output power and lithium battery capacity based on neural network.For the existing photovoltaic data set and CALCE lithium battery data set,CNN and LSTM are used to establish a multi-layer neural network model for performance prediction.The results show that the model can effectively predict the performance and state of solar cells and lithium batteries.To sum up,this research mainly focuses on the simulation and state prediction of the micro-nano satellite power supply subsystem based on multi-physical quantity coupling.By establishing a multi-physical quantity coupling relationship model,the power supply subsystem is simulated,and the power supply state is predicted by neural network.