Study on SOC estimation method for mine backup power supply

This paper focuses on nickel metal hydride batteries that are monomers. By increasing the adaptive rate of BP neural networks, the batteries can increase discharge, with temperature, current, and end voltage acting as the network's input characteristics. Nickel metal hydride batteries are the primary backup battery used in mining power supplies. Their high stability and energy density make them ideal for improving battery SOC (charge) estimation accuracy and prolonging service life at the same time. In accordance with the difference between the training sample's actual and expected output, adjust the momentum term; in accordance with the backpropagation error's direction change, raise the adaptive learning rate. In contrast to the traditional BP neural network approach, there was a 78% increase in convergence speed and a steady estimation error within 10%.