About Retired power battery energy storage
Figure 2(1) shows the results of predicting RUL using the BP neural network method for the NASA dataset B0005 battery. It can be seen that the BP neural network algorithm used in this paper can achieve accurate prediction within 0.015 error, and has the ability to continue to evaluate as an evaluation index.
Firstly, a comparison matrix A about RUL, SOC and \(\Delta T\)three evaluation indicators established according to the AHP analytic hierarchy process-five-scale.
Based on the comprehensive safety assessment model of the energy storage system proposed in this paper, the risk score is solved, and the real-time risk score.
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