A Neural Approach to Estimate the Radiation Damage of the Solar Panels


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Abstract


Solar cells in space are damaged by exposure to energetic protons and electrons. These particles pass through protective coverings and disrupt delicate crystal lattices. The output power of the system is continuously degraded over the mission life. Space power engineers need damage coefficients to predict solar cell power degradation. So, the modelling of solar cells constitutes a research field that is currently very important throughout the world. To continue this evolution, the existing models must be improved and new models have to be developed. In this paper, we present the applicability of the artificial neural network (ANN) for the study of the radiation damage of the solar cells and the development of a neural model  allows the evaluation of  the  degradation of the solar cells parameters (series and parallel resistance, diode coefficient, reverse current density,…) under a given irradiation and space fluence. Our results are compared with the experimental ones, analysed and discussed in order to obtain some useful information about the use of the solar cells in space environment.
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Keywords


Solar Cell Parameters; Artificial Neural Network, Radiation Damage; Degradation

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