Satellite power supply system

Abstract

A satellite power supply system comprises a photoelectric conversion module, the photoelectric conversion module comprises a plurality of photoelectric conversion groups, a troubleshooting part is arranged in each photoelectric conversion group, when the troubleshooting parts are connected, solar cells connected with the troubleshooting parts in parallel are eliminated from power supply lines of the photoelectric conversion groups, and the output end of each photoelectric conversion group is provided with an MPPT unit; an MPPT algorithm is utilized to maintain the output power of a photoelectric conversion group at the maximum output power point, and an energy management module maintains the maximum output power point in a required state according to the current satellite electricity generation power requirement in a mode of adjusting the posture of the photoelectric conversion group.

Description

Technical field [0001] The present invention relates to a power module used in satellites, and more particularly to a satellite power supply system. Background technique [0002] Microsatellites have become the main development direction of China's aerospace technology in the advantages of small size, light, low cost, etc., and short-term development cycle, facilitating modularity and batch production. [0003] The development of commercial space, requires a well-adaptive and scalability for commercial satellites. As the core components of the satellite system, the satellite energy system has the same design requirements for wide and scalability. [0004] Satellite power system is one of several major core systems of satellite. Satellite inward is accompanied by alternating battery and solar cell array. When the battery array can meet the power supply, the power of the satellite is provided by the solar battery array. At this time, the battery is charged; when the solar cell arra...

AI Technical Summary

Problems solved by technology

Model-based diagnosis is to establish an accurate model of the power system, and detect abnormalities from the model and measurement data; artificial intelligence diagnosis methods mainly include expert systems and neural network methods, etc. The expert system is to establish an experience database based on the experience of experts. The extracted features are compared with the features in the experience database to achieve the purpose of anomaly detection. The artificial neural network self-learns the historical anomaly and normal data, but there are many defects in the existing methods. First, the measurement parameters used are too high. There are many parameters, and the physical meaning of the parameters is not obvious. Second, the effect of early anomaly detection is not obvious. Third, it is impossible to actively intervene before the failure occurs, reducing the probability of failure and prolonging the service life of the battery.

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